Ecology in Agriculture (Physiological Ecology)

Ecology in Agriculture

This is a volume in the PHYSIOLOGICAL ECOLOGY series Edited by Harold A. Mooney A complete list of books in this series appears at the end of the volume.

Ecology in Agriculture Edited by

Louise E. Jackson Department of Vegetable Crops University of California, Davis Davis, California

Academic Press San Diego

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Grape vines photo by Rich Knauel.

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Copyright 9 1997 by ACADEMIC PRESS All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Academic Press a division of Harcourt Brace & Company 525 B Street; Suite 1900, San Diego, California 92101-4495, USA http://www.apnet.com Academic Press Limited 24-28 Oval Road, London NWl 7DX, UK http ://www.hbuk.co.uk/ap/ Library of Congress Cataloging-in-Publication Data Ecology in agriculture / edited by Louise E. Jackson. p cm. -- (Physiological ecology) Includes bibliographical references and index. ISBN 0-12-378260-0 (hardcover : alk. paper) 1. Agricultural ecology. I. Jackson, Louise E. II. Series. $589.7.E255 1997 97-25875 630'.1'577--dc21 CIP

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Contents

Contributors Preface xi

ix

Part I Plant Responses to the Environment 1. The Ecophysiology of Crops and Their Wild Relatives Louise E. Jackson and George W. Koch

I. Introduction 3 II. Domestication 4 III. Environmental Considerations and Agricultural Selection Strategies 8 IV. Comparison of Crops and Their Wild Relatives V. Potential Contribution of Wild Germplasm to Crop Ecophysiology 27 VI. Concluding Remarks 31 References 32

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2. Photosynthesis, Growth Rate, and Biomass Allocation Vincent P. Gutschick

I. II. III. IV. V. VI.

Introduction 39 Basic Concepts 40 Some Detailed Adaptive Responses of Photosynthesis 49 Use of Photosynthate and Adaptive Patterns Therein 62 Synthesis and Conclusions 68 Appendix: Correspondence of Variables with Those of Condon and Hall 70 References 71

3. Adaptation to Diverse Environments: Variation in Water-Use Efficiency within Crop Species A. G. Condon and A. E. Hall

I. Introduction 79 II. Mechanisms of Genotypic Variation in Water-Use Efficiency 81 III. Theoretical Associations between Leaf Gas-Exchange Efficiency and Adaptation 88

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Contents

IV. Empirical Observations 91 V. Critical Research Needs and Conclusions References 111

109

4. Productivity in Water-Limited Environments: Dryland Agricultural Systems

C. Gimenez, F. Orgaz, and E. Fereres I. Introduction 117 II. Characterization of Water-Limited Environments 119 122 III. Water Use and Water-Use Efficiency IV. Carbon Partitioning to Harvestable Yield 127 V. Integration of Responses in Dryland Agricultural Systems VI. Conclusions 137 References 137

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5. Nitrogen as a Limiting Factor: Crop Acquisition of Ammonium and Nitrate Arnold J. Bloom I. Importance of Nitrogen Acquisition 145 II. Physiology of Root Ammonium Acquisition 146 III. Physiology of Root Nitrate Acquisition 153 IV. Plant Growth as a Function of Ammonium or Nitrate References 164

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6. Trade-offs in Root Form and Function

David M. Eissenstat I. Introduction 173 II. Citrus as a Model System 174 III. Optimizing Carbon Expenditure on Roots 175 IV. Parallels between Roots and Leaves 177 V. Specific Root Length, Root Diameter, and Tissue Density VI. Exploiting Soil Heterogeneity 180 VII. Root Architecture 183 VIII. Root Hydraulic Conductivity 186 IX. Root Herbivory and Root Defense 189 X. Mycorrhizae 190 XI. Root Life Span 193 XII. Summary and Conclusions 194 References 195

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Part II Biotic Interactions and Processes 7. The Use of Biodiversity to Restrict Plant Diseases and Some Consequences for Farmers and Society Maria R. Finckh and Martin S. Wolfe I. Introduction 203

Contents

II. III. IV. V. VI. VII. VIII.

The Pathologist's View 204 The Breeder 218 The Farmer 223 The Agronomist/Adviser 223 The Consumer 225 Politicians and Economists 227 Society at Large and Future Perspectives References 229

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8, Plant-Arthropod Interactions in Agroecosystems D. 14. Letoumeau

I. Introduction: ~'ops as Resources 239 II. Ecological Consequences of Economically Driven Decisions: The Grower's Perspective 240 III. Exploitation Strategies: The Herbivore's Perspective 241 IV. Ecological and Evolutionary Antiherbivore Strategies: The Plant's Perspective 243 V. Crop Protection: An Ecological Perspective 271 References 276

9. Many Little Hammers: Ecological Approaches for Management of Crop-Weed Interactions Matt Liebman and Eric R. Gallandt

I. II. III. IV. V. VI.

Introduction 291 Information and Approaches 293 Basic Principles Guiding Weed Management Strategies Managing Crop-Weed Interactions 307 Many Little Hammers 325 Summary and Conclusions 329 References 330

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Part III Ecosystem Processes 10. Nitrogen Use Efficiency in Row-Crop Agriculture: Crop Nitrogen Use and Soil Nitrogen Loss G. Philip Robertson

I. II. III. IV. V.

Introduction 347 Crop Nitrogen Demand 351 Matching Nitrogen Availability to Demand 353 Major Pathways of Nitrogen Loss from Cropping Systems Management to Maximize Nitrogen Use in Row-Crop Ecosystems 361 References 362

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11. Soil Microbial Communities and Carbon Flow in Agroecosystems Kate M. Scow I. II. III. IV. V. VI. VII.

Introduction 367 Carbon Flow at the Cellular Level 369 Carbon Flow: Populations and Communities 377 Carbon Flow at the Soil Level 382 Quantitative Descriptions of Carbon Flow in Soil 393 Comparison of Agricultural to Other Ecosystems 396 Impacts of Soil Carbon-Microbial Interactions on Agroecosystems 397 VIII. Conclusion 402 References 403

12. Effects of Global Change on Agricultural Land Use: Scaling Up from Physiological Processes to Ecosystem Dynamics Rik Leemans I. II. III. IV. V. VI. VII.

Introduction 415 Global Modeling of Ecosystem and Crop Patterns 418 Feedbacks in the Earth's System 433 Integrated Modeling of Global Environmental Change 436 Concluding Remarks 445 Summary 446 Appendix: Direct Effects of Increased CO2 Concentrations on Plant Growth 447 References 448

Index

453

Contributors

ArnoldJ. Bloom (145), Department of Vegetable Crops, University of California, Davis, Davis, California 95616 A. G. Condon (79), CSIRO, Division of Plant Industry and Cooperative Research Centre for Plant Sciences, Canberra, ACT 2601, Australia David M. Eissenstat (173), Department of Horticulture, The Pennsylvania State University, University Park, Pennsylvania 16802 E. Fereres (117), Department of Agronomy, University of Cordoba, and Institute of Sustainable Agriculture (CSIC), Cordoba 14080, Spain Maria R. Finckh (203), Institute of Plant Sciences, Swiss Federal Institute of Technology, CH-8092 Z~rich, Switzerland Eric R. Gallandt (291), Department of Applied Ecology and Environmental Sciences, University of Maine, Orono, Maine 04469 C. Gimenez (117), Department of Agronomy, University of Cordoba, Cordoba 14080, Spain Vincent P. Gutschick (39), Department of Biology, New Mexico State University, Las Cruces, New Mexico 88003 A. E. Hall (79), Department of Botany and Plant Sciences, University of California, Riverside, Riverside, California 92521 Louise E.Jackson (3), Department of Vegetable Crops, University of California, Davis, Davis, California 95616 George W. Koch (3), Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona 86001 Rik Leemans (415), National Institute of Public Health and the Environment (RIVM), NL-3720 BA Bilthoven, The Netherlands D. K. Letourneau (239), Department of Environmental Studies, University of California, Santa Cruz, Santa Cruz, California 95064 Matt Liebman (291), Department of Applied Ecology and Environmental Sciences, University of Maine, Orono, Maine 04469 F. Orgaz (117), Department of Agronomy, University of Cordoba, Cordoba 14080, Spain G. Philip Robertson (347), W. K. Kellogg Biological Station and Department of Crop and Soil Sciences, Michigan State University, Hickory Corners, Michigan 49060

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Contributors

Kate M. Scow (367), Department of Land, Air, and Water Resources, University of California, Davis, Davis, California 95616 Martin S. Wolfe (203), Institute of Plant Sciences, Swiss Federal Institute of Technology, CH-8092 Zfirich, Switzerland

Preface

An ecological viewpoint of agriculture focuses on describing the relationship between organisms and their biotic and abiotic environments and on understanding the biological processes that control the distribution, behavior, and fitness of individuals; the interactions between organisms; and the flow of materials and energy through the agricultural ecosystem. The intent of this book is to illustrate how the fundamental principles of ecology operate in agricultural settings and how they can be applied to solve practical problems in crop production and environmental management. In the past few years, agricultural research has moved toward an increasing emphasis on long-term sustainability of food and fiber production, environmental quality, and ways to promote ecosystem health. These are complex topics. Such new research approaches require a scope broader than the traditional agronomic approach of maximizing yields with efficient use of resource inputs. Ecological principles and methodologies have been helpful in addressing these issues. It has been necessary, however, to bridge a long-standing gap between the two disciplines of ecology and agronomy to find practical solutions to such agricultural problems as minimizing inputs of limited resources, decreasing pesticide application by exploiting biological mechanisms of pest reduction, and mitigating long-term changes in soil and environmental degradation. Ecological processes in agricultural settings can be examined at several hierarchical levels. Autecology concerns the relationships of organisms to their environment and the processes that regulate water and nutrient use, productivity, and crop yield. Community ecology is the study of interactions between organisms, including processes such as parasitism, predation, and competition involving crop plants and populations of pathogens, insect pests, and weeds. Systems ecology encompasses a broader scope of interactions and considers how biotic and abiotic processes control the flow and availability of carbon and nutrients in the ecosystem as a whole. Ecophysiological responses of crops to the environment are a result of direct selection by breeders for traits to increase yield and yield reliability, as well as of inadvertent selection for successful adaptation to specific agricultural environments. During crop evolution, most of the differences in ecophysiology can be attributed to changes in the regulation of development and resource partitioning rather than to changes in rates of assimila-

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Preface

tion and nutrients. There are some inherent constraints on maximizing photosynthesis due to ability to acquire light, CO2, water, and nutrients that may explain this observation. Optimization of crop growth and yield can best be achieved by considering cost-benefit analyses of resource acquisition and allocation and by studying trade-offs between whole plant integrated responses to stress in genotypes from different agricultural environments. Community ecology in crop fields is actually very complex in time and space, despite the lack of plant diversity in most agricultural ecosystems. For example, there are many strategies by which herbivores exploit crops and by which crops defend themselves, indicating complicated evolutionary and ecological relationships that must be considered in developing crop protection methods using ecological approaches. Ecologically based management of pathogens, insect pests, and weeds tends to invoke methods that increase spatial, temporal, and community diversity and to require multiple approaches to avoid deleterious effects of other organisms on crop plants. Ecosystem processes in agriculture require an understanding of smalland large-scale interactions between organisms and their environment and of how the integrated behavior among all biota controls the assimilation, transfer, and losses of carbon and nutrients from the ecosystem. Detailed information of this nature is relatively scarce, especially for community structure and function of soil organisms. This often necessitates lumping organisms into functional groups and recognizing that some elements of spatial and temporal diversity must be overlooked in the effort to find an appropriate scale for expressing flows and transformations of materials. A better grasp of system-level processes promises solutions to such problems as maintaining soil quality over the long term, reducing groundwater pollution due to agricultural practices, and predicting the response of agriculture to atmospheric changes and global warming. Our goal for this book is to highlight examples of ecological approaches to studying agriculture at these three levels. We deal only with crop-based agriculture and not with animal production. It has not been possible to cover every important topic, but we hope that the book will provide insight on concepts, patterns, and methodology for examining ecology in an array of agricultural settings. LOUISE E. JACKSON

I Plant Responses to the E n v i r o n m e n t

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1 The Ecophysiology of Crops and Their Wild Relatives

Louise E. Jackson and George W. Koch

I. Introduction Domestication of wild plants for human utilization involved changes in selection pressures and, consequently, in population structure and in evolution of traits associated with resource acquisition, allocation, and reproduction. Selection by crop breeders emphasizes yield, yield stability, and yield per unit resource applied, whereas natural selection operates to continue the survival of species, emphasizing traits that may be at odds with breeders' goals. Criteria for fitness change dramatically under the two selection regimes. In wild populations, seed or propagule production and dissemination are the most important attributes that define the fittest individual (i.e., the individual that leaves the greatest number of descendants). With agricultural selection, production of harvestable yield is the prime consideration for fitness. Even when the seed is the harvestable unit, yield rather than survivorship in the next generation is the most important factor in selection. The two selection processes have fundamentally different implications for plant growth and allocation of resources. Ecophysiological differences between crops and their wild relatives depend on the taxa compared. In many cases, crops are completely interfertile with their putative progenitors [e.g., cultivated and wild lettuce, Lactuca sativa and L. serriola, which should be considered conspecific (Kesseli et al., 1991)] despite large morphological and genetic differences. Reproductive isolation is maintained between these plants by human cultural practices, Ecology in Agriculture

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Copyright 9 1997 by Academic Press. All fights of reproduction in any form reserved.

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Louise E. Jackson and George W. Koch

and they are best viewed as populations of a single species subject to diversifying and directional selection. In some cases, selection has advanced so far that the wild progenitor of a crop is not known (e.g., maize until recently), and hybridization with close relatives results in sterile or no offspring. These examples yield less useful information on ecophysiological changes during crop evolution because comparison with immediate progenitors is impossible and the closest extant relative may not share a common environment of origin. The purpose of this review is to examine the ecological origins of crop plants and to assess the impact of domestication and subsequent agricultural selection on physiological processes and ecologically important traits including rates of photosynthesis and nutrient acquisition, resource allocation patterns, and phenological schedules. The focus is on crops derived from Mediterranean annual species, due to the availability of information for these plants. From an ecological point of view, comparison of crops and wild relatives expands our understanding of evolution and adaptation to the environment when plants of similar genetic backgrounds are subject to differences in selection pressures. From a practical perspective, such information helps to identify successful strategies for purposeful selection of crops growing under various management regimes and indicates possible pitfalls in direct selection for physiological traits in breeding programs. We first discuss the process of domestication of plants, reviewing what is known about the origin of crops as wild species and the various pathways of genotypic and phenotypic change leading to early cultivars. Next, we review the strategies of selection for crop improvement, emphasizing the trade-offs between selection for maximal yields under high-input conditions and relatively stable yield across a range of environments. Several case studies of the comparative ecophysiology of crops and their wild relatives serve to illustrate the idea that physiological features have been generally conserved during domestication and selection, whereas changes in morphological characteristics have been more amenable to change and have contributed to much of the improvement in yield. We conclude by speculating about the potential for extant wild germplasm to contribute to further improvements in crops in the face of changing demands on modern agricultural ecosystems.

II. D o m e s t i c a t i o n A. Crop

Origins

The progenitors of many of the crops grown in the temperate, northern hemisphere were ruderal species native to frequently disturbed areas in the Mediterranean Basin. Examples include wheat, barley, oat, sunflower,

I. Ecophysiology of Crops and Their Wild Relatives

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radish, and lettuce (Smartt and Simmonds, 1995). Many ruderal species share attributes such as (1) high rates of resource acquisition and vegetative growth, (2) allocation patterns that respond flexibly to changing resource availability, (3) low levels of defensive chemicals, (4) early onset of reproduction, (5) self-compatibility, (6) high seed production, (7) adaptations for short- and long-distance dispersal, and (8) variable seed dormancy (Baker, 1974; Chapin, 1980). Some of these attributes are obviously advantageous for crops in cultivated environments (termed preadaptations), whereas others, such as variable seed dormancy, are clearly problematic for maximizing harvestable yield. In general, early successional species have a greater breadth of response for such parameters as germination, survivorship, and growth to gradients of resource availability than do species typical of later successional stages (Bazzaz, 1987). Large niche breadth means that these species can establish and survive in unpredictable environments such as those that occur in disturbed or sparsely occupied sites. B. Pathways of Domestication A broad definition of plant domestication is given as " h u m a n intervention in the reproductive system of the plant, resulting in genetic a n d / o r phenotypic modification" and domestication of wild plants is thought to have occurred through three main types of pathways (Harris and Hillman, 1989, as cited in Frankel et al., 1995): (1) "plastic" phenotypic change from somatic genetic change, involving vegetative propagation; e.g., root and tuber crops such as yam, or cross-pollinated fruit species; (2) gradual genotypic change, involving outbreeding taxa, e.g., beets, carrots, and other vegetables; and (3) rapid genotypic change, involving inbreeding taxa; e.g., cereal and legume domestication in the Near East. The first pathway of domestication concerns clonal propagation of perennial plants as a rapid means to domesticate native plants with desirable characteristics. Reliance on vegetatively propagated plants, such as yams, sweet potatoes, and bananas, was common in indigenous agricultural systems in the warm, humid tropics possibly due to the higher success of growth and establishment of plants from buds, rhizomes, and stems in this type of environment. In temperate fruit crops that are cross-pollinated, such as olive, figs, and apples, vegetative propagation and grafting were solutions to the problems of wide genetic segregation with sexual reproduction. A slower process of domestication occurred for cross-pollinated plants that were only capable of reproducing by seed. Populations of plants with an outbreeding reproductive system are composed of many heterozygous genotypes, which may be different from one another (Hamrick and Godt, 1989). Cross-pollination results in a new assembly of genotypes in each generation, but each of these assemblies will be on average similar from

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Louise E. Jackson and George W. Koch

one generation to the next. Breeding of cross-pollinated crops can be done by increasing the frequency of those genes in the gene pool that produce a higher frequency of superior genotypes, but this can be a slow process that requires mass selection of bulked seed from several superior plants (Briggs and Knowles, 1967). In outcrossing plants, selection for homozygotes typically leads to loss of vigor. Control of cross-pollination is a recent development to create inbred lines for producing vigorous hybrids. In taxa subject to the third pathway of domestication, the inbreeding reproductive system would have hastened the selection process for successful domestication. Self-pollinating plants breed true, facilitating perpetuation of superior genotypes and retention of preadaptive traits that were conducive to cultivation (Hawkes, 1983; Zohary and Hopf, 1988; Evans, 1993). Low levels of outcrossing [e.g., typically < 1% in Near Eastern wild wheats (Hillman and Davies, 1990)] would have supplied genetic variation for further selection. A trait in the cereals and grain legumes in the Near East (e.g., einkorn and emmer wheat, barley, peas, lentils, chickpeas, and bitter vetch) that could be considered preadaptive is the production of seeds with large, edible storage reserves. It apparently evolved as a mechanism for these annual plants to grow rapidly during the sporadic rains at the end of the long summer drought (Zohary and Hopf, 1988). The predominantly inbreeding mating system of these crops would have facilitated the selection of new, desirable traits, such as more uniform germination, and in the annual cereal crops, a nonbrittle rachis that prevented shattering of the inflorescence and scattering of the seed with ripening. In this case, grains were probably harvested at unripe stages until homozygous recessive mutants with the semitough rachis trait were discovered (Hillman and Davies, 1990). Thereafter, fixation for this trait could have theoretically occurred in 20-30 years, greatly enhancing recovery of grain. Another aspect of inbreeding that affected domestication is the possibility of local genetic differentiation in response to variation in natural habitats (Heywood, 1991). For example, high site-to-site environmental variability would be expected given the wide span of ecological habitats in which the progenitors of cereal grains are hypothesized to have been distributed (Harlan and Zohary, 1966). In Mediterranean annual species, genetically distinct ecotypes occupy specific niches so that there is a close association between certain genotypes and microhabitats. For example, in Avena barbata in Israel, where it is endemic, and in California, where it was introduced 300 years ago, distinct phenotypes and combinations of allozymes occur in "xeric" and "mesic" habitats (Hamrick and Allard, 1972, 1975; Kahler et al., 1980). Research in Israel has shown that wild wheat ( Triticum turgidum ssp. dicoccoides) shows high genetic diversity between and within populations, indicating a capacity for microsite specificity and responsiveness to the high interannual variation in weather (Nevo et al., 1982, 1991; Carver and Nevo,

1. Ecophysiology of Crops and Their Wild Relatives

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1990). This situation would have provided variation from which early plant breeders could choose, allowing selection of genotypes suitable for a wide range of agricultural settlements. In early selections of self-pollinating large-grained annual grasses for cultivation, humans had to deal with growth patterns and genetic population structures that ensured success in a variable climatic regime. For example, human selection increased the uniformity of seed production within single plants and within populations by increasing genetic similarity. There may also have been selection for reduced phenotypic plasticity, which would be expected to be high initially in ruderal species adapted to temporally and spatially heterogeneous environments (Grime, 1994). In fact, phenotypic plasticity in traits related to productivity, such as number of fillers and shoot dry weight, is very high in wild wheat, T. turgidum ssp. dicoccoides (Anikster et al., 1991). Prolonged flowering and a protracted reproductive phase are likely to increase the variability in allocation to vegetative and reproductive structures among plants in a population, especially if shortterm stresses occur intermittently during the life cycle (Chiariello and Gulmon, 1991). In wild annual grasses from the Mediterranean Basin, such as Bromus mollis, translocafion of carbon into the developing inflorescences and senescence of vegetative tissue occur gradually so that all stored reserves are not immediately invested in seeds during early developmental stages of inflorescences that may or may not make it to maturity (Jackson et al., 1987). In wild barleygrasses (Hordeum spp.), new inflorescences are still emerging while seeds are dehiscing from older inflorescences (Chapin et al., 1989). In wild plants, selection for asynchronous development of reproductive structures on a single plant would be more likely than uniform maturation to assure production of offspring under variable conditions, but uniform maturation is a valuable attribute for cultivated production. Another example of changes in growth patterns with domestication is in the timing of vegetative and reproductive allocation. Annual plants in environments with predictable periods of stress, such as the summer drought in regions with Mediterranean-type climates, typically show a fairly sharp transition from vegetative to reproductive growth (Chiariello and Gulmon, 1991). With the removal of the end of season stress by provision of nutrients and water, we might expect selection to favor genotypes that retain the ability to continue vegetative growth after the onset of reproduction, thereby prolonging the period of resource acquisition and enhancing seed output. In outbreeding species, archaeological evidence indicates that the domestication process was much slower. For example, the earliest cultivated maize is essentially genetically identical to the oldest accession of wild maize, which occurred nearly 2000 years earlier (Doebley, 1994). Heterozygosity and variability do result from cross-pollination, causing a new assemblage

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Louise E. Jackson and George W. Koch

of gene recombinations to occur in each generation, but on the average these assemblages will be similar from generation to generation, as long as genetic material is not lost from or introduced into the population (Briggs and Knowles, 1967). Outcrossing increases genetic heterogeneity in and among populations (Hamrick and Godt, 1989), and most populations of outcrossing plants show relatively low levels of microspatial genetic structuring, which limits the ability for humans to select potentially desirable genotypes from natural plant communities.

III. Environmental Considerations and Agricultural Selection Strategies For many crops, there has been a gradual change from their use in subsistence farming to intensive large-scale commercial farming operations. This progression has generally, although not always, been accompanied by increased inputs of water, fertilizer, and pesticides to reduce the risk of crop failure. Plant resource availability was initially greater in early agricultural sites than in the ecosystems from which crop progenitors originated because these sites were located in more resource-rich areas such as floodplains and lake margins (Delcourt, 1987). Light availability would have increased due to removal of competitors, although planting densities may have had an opposing influence. As inputs have continued to increase up to the present day, yields have increased, but so has the annual variability in yield; this can be attributed to several factors including greater responsiveness of modern varieties to resource inputs and increased susceptibility and impact of pest outbreaks on more genetically uniform plantings that is caused by widespread adoption of a few varieties (Anderson and Hazell, 1989). The advent of agriculture also involved changes in the ecological setting of cultivated species because they were planted in stands or had their interspecific competitors removed. In ancient agricultural sites in Europe and North America, the pollen record shows that forest trees declined while ruderal species increased, and that perennial ruderal species such as grasses and plantains decreased after the development of the plow (Delcourt, 1987). Reduced interspecific competition favored the spread of annual crops and more frequent crop rotation. Forest clearing and transition of shrublands to pastures by grazing also permitted the establishment of horticultural trees from beyond their native ranges. For example, the distribution of pistachios and olives extended throughout southern Europe after 3000 BP, away from their native habitats in coastal areas along the Mediterranean Sea (Delcourt, 1987). Thus, human land use promoted changes in range expansion of early horticultural taxa.

1. Ecophysiology of Crops and Their Wild Relatives

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Although resource availability to crop plants has generally increased through time, in situations in which low-input, subsistence agriculture has persisted, landraces have been systematically selected for performance in adverse and variable environments. [A landrace is defined as a set of populations (or clones) of a crop species with distinct morphological characteristics that are maintained by farmers, who recognize them as all belonging to the same entity (Harlan, 1975)]. Under low-yielding conditions, yields are often highly variable, and so the main breeding objective is yield stability or reliability to minimize the likelihood of crop failures (Ceccarelli et al., 1991). For example, in Bavaria, an old landrace of barley outyielded a modern cultivar in low-input farming systems because its longer straw provided better competition against weeds, but with present-day farming methods, the yield of the modern cultivar was much higher than the landrace (Fischbeck, 1989). In all farming systems, the Bavarian landrace had a lower coefficient of variation for yield. In another example, a landrace of maize in Malawi was less responsive to environmental conditions (as measured by an environmental index equal to the average yield of all treatments at each location) than a modern variety, but the landrace performed better on the poorer sites (Hildebrand, 1984). Similar results were observed between barley selections made at high-yielding (i.e., expected yields of 3-5 t ha 1, average rainfall of 332 mm) and low-yielding (i.e., expected yields of 1 t ha -a, average rainfall of 201 mm) environments in Syria without supplemental irrigation (Ceccarelli and Grando, 1991). Genotypes developed through repeated selection in low-yielding environments had a higher probability of producing high yields under low-yielding conditions than genotypes selected under high-yielding environments (Fig. 1). Because they produce poorly under high-yielding environments, their performance was more similar across a range of environmental conditions. Landraces of barley from low-yielding environments in Syria tend to have a prostrate habit, cold tolerance, a short grain filling period, low early vigor, and late heading. These attributes promote successful establishment and growth during the cold winter and into the drying spring growing season so that good yields are produced in most years, but would presumably constrain growth in warmer, moister, and more fertile conditions, in which a longer period of reproductive growth would be advantageous (Ceccarelli et al., 1991). These results suggest that one avenue toward yield reliability is a growth cycle that assures a moderate amount of productivity under lowyielding conditions but that inherently limits the ability to produce well under more favorable conditions. Another avenue is that these landraces are genetically heterogeneous and are composed of an assemblage of genotypes, each with a different combination of traits that are likely to be advantageous for specific combinations of environmental stresses that occur in this region of highly variable climatic conditions (Ceccarelli, 1994).

10

Louise E. Jackson and George W. Koch /~ High grain yield under high yielding conditions (genotype 1) ..-. 6"7, .r 5t'-

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F(slopes)-8.8 (P 2.8) TE values decreased by about half as irradiance doubled. Unfortunately, the effects of VPD and of increasing irradiance were not separated in Kanemasu's (1983) study. In situations of near complete radiation interception by the crop, the VPD is the governing factor affecting TE. However, under low LAI values, irradiance must play an important role in determining TE, interacting with the fraction of total leaf area that receives radiation levels above the saturation point. Management practices directed at increasing TE must attempt to maximize the radiation intercepted by the crop during the periods of low irradiance and VPD. Once again, early plantings and any other practice promoting early growth (planting density, fertilization, early vigor, etc.) will increase biomass production in Mediterranean-type environments not only through a reduction in E, as it was argued in Section III,A,2, but also through an increase in TE.

IV. Carbon Partitioning to Harvestable Yield In many DASs, harvestable yield includes all aboveground biomass, particularly in the crop-livestock systems on drier areas. In all other cases, harvestable yield is only a plant part and the processes of assimilate partitioning and C allocation are of paramount importance for the determination of final yields. Empirical selection for yield has increased the partitioning to harvestable organs but our understanding of the processes that determine dry matter distribution is very limited. A. Dry Matter Distribution under Water Deficits Water deficits affect the partitioning of dry matter to above- and belowground plant parts. The functional balance between shoot and root (Brouwer, 1983) is altered by water stress in the direction of a relative increase in carbon partitioning to the root. Another relevant partitioning process that is affected by water deficits is the distribution of dry matter between vegetative and reproductive organs. Both responses have an effect on the productivity of DASs as discussed below.

1. Leaf Area and Root Growth Yield decreases caused by water deficits are primarily mediated by the reduction in leaf area. Numerous studies in various crops, such as maize and sorghum (Hsiao et al., 1976), wheat (Robertson and Giunta, 1994), sunflower (Connor and Jones, 1985; Gimenez and Fereres, 1986), faba bean (Karamanos, 1984), cotton (McMichael et al., 1973), soybean and sorghum (Constable and Hearn, 1978), and barley

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(Day et al., 1987), have shown how water deficits effect large reductions in leaf area that are directly linked to a decrease in intercepted radiation and in yield. Passioura (1994) has emphasized the role of leaf area in the modulation of yield under water deficits. Leaf expansion rates (LER) are immediately reduced by water deficits (Acevedo et al., 1971). In the longer term, however, it appears that leaf area expansion under water deficits is modulated via chemical signals sent by the roots (Passioura, 1994). However, the role of the shoot water status has been shown to be critical in at least one field experiment (Sadras et al., 1993) in which variations in VPD affected the relation between LER and soil water status. It is probable that both hydraulic and hormonal signals interact somehow in determining the patterns of leaf expansion under water deficits (Tardieu, 1993). Mild water deficits, while reducing leaf area, must make available additional C for other plant processes, including root growth. This is because photosynthetic processes are less sensitive to water deficits than is LER. Root extension into new soil is less affected by water deficits than LER, and that provides a feedback mechanism for the improvement of growth and water status of the shoot. The traditional view is that large, vigorous root systems are advantageous in water-limited environments. Actually, roofing depth is directly related to water extraction (Ehlers et al., 1991), whereas there are substantial differences in rooting density (Lv) among crops (Hamblin and Tennant, 1987) and cultivars (Gregory, 1994) often not related to differences in water uptake. Although differences in Lv among species are of interest for complete exploitation of available resources in a given environment, genotypic differences are mostly linked to maturity date (Blum and Arkin, 1984). For example, long-season sunflower varieties depleted the deeper layers of the profile much more than early cultivars (Fig. 2; Gimenez and Fereres, 1986). The additional water captured by the deeper root systems of late-maturing cultivars occurs near the end of the season, when evaporative d e m a n d is highest in Mediterranean-type environments. Thus, TE values are low and that may reduce the benefits of the higher Toflate cultivars (Fig. 3; Fereres, 1987). Such cultivars are best suited to areas of deep soils that must be consistently refilled by seasonal rainfall if their use is to be sustainable. The maintenance of green leaf area and root growth under water deficits is an important feature contributing to mitigate drought impacts on yield. Osmotic adjustment (Hsiao et al., 1976) maintains root growth, slows down leaf senescence (Hsiao et al., 1984), and promotes assimilate translocation to the grains (Ludlow et al., 1990). Despite earlier criticism (Munns, 1988), it is now firmly established that osmotic adjustment is a valuable adaptive feature of crops and cultivars adapted to water-limited environments (Ludlow and Muchow, 1990; Tangpremsri et al., 1995).

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Figure 2 Soil water extraction for (a) A1 x R2 (&) and Contiflor (O) in 1981 and (b) A1 X R7 (O) and Sungro ([]) in 1983. Measurements are average of four replicates. A1 X R2 and A1 X R7 are short-season genotypes and Contiflor and Sungro are long-season genotypes (from Gimenez and Fereres, 1986).

2. Mobilization o f Reserves Mobilization of reserves to harvestable o r g a n s in r e s p o n s e to water deficits c h a n g e s t h e d i s t r i b u t i o n o f dry m a t t e r in the p l a n t a n d d i m i n i s h e s t h e i m p a c t of water stress o n yields. S u c h adaptive r e s p o n s e has b e e n t h o r o u g h l y d o c u m e n t e d in w i n t e r cereals, in which the m o b i l i z a t i o n o f p r e a n t h e s i s assimilates s t o r e d in leaves a n d s t e m is e n h a n c e d by water deficits. G a l l a g h e r et al. (1975) e s t i m a t e d in barley t h a t p r e a n t h e s i s assimilation

Figure 3 Relationships between evapotranspiration and (a) biomass and (b) grain yield for five early (open symbols) and five late (closed symbols) sunflower cultivars. Data obtained at Cordoba, Spain, between 1981 and 1985 (from Fereres, 1987).

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contributed 2% of grain yield in a wet year but up to 74% in a very dry year. This contribution was calculated as the dry weight difference between anthesis and maturity of the vegetative aboveground organs. This methodology overestimates the mobilization of reserves because the dry weight change in the nongrain parts includes tissue losses (mainly leaves) due to wind, decay, etc. Bidinger et al. (1977) used labeled 14CO2 at frequent intervals before and after anthesis to estimate that 20% of preanthesis assimilates were transferred to grain in water-stressed wheat. Austin et al. (1980) estimated that the mobilization of preanthesis reserves in barley was 44% of grain yield in a dry treatment and just 11% when water was not limiting. Not only does the relative proportion of preanthesis assimilation increase but also some studies (Palm et al., 1994) showed that water deficits effected an absolute increase in the contribution of preanthesis reserves to wheat yield. Breeders have searched for genetic variability in this favorable character. Blum et al. (1983), using magnesium chlorate as a dessicant, attributed the difference among four spring wheat cultivars in sustaining kernel growth in the absence of photosynthesis to differences in stem reserves mobilization. Magnesium chlorate has been found to be too severe a dessicant to simulate d r o u g h t effects by Turner and Nicolas (1987), who proposed the use of potassium iodide as a more suitable chemical. Mahalakshmi et al. (1994) have succesfully used this senescing agent in pearl-millet by spraying with KI at anthesis as a screening m e t h o d to evaluate the genetic variability in reserve mobilization u n d e r water deficits during grain filling. The general conclusion is that assimilate mobilization increases yield stability in drought situations by acting as a buffer against the detrimental effects of water deficits on postanthesis assimilation. Genetic variability in reserve mobilization has also been reported in soybean (Constable and Hearn, 1978) and sorghum (Ludlow et al., 1990). This adaptative trait could be incorporated into new varieties to increase crop yield u n d e r waterlimited environments. Attempts to use chemical desiccation to select lines u n d e r simulated postanthesis stress have been relatively successful in cereals (Nicolas and Turner, 1993). B. Effects o f Water Deficits on the Harvest I n d e x 1. H a r v e s t Index The effects of water deficits on HI d e p e n d on the timing and intensity of water stress. Mild water deficits either do not alter the HI value or, exceptionally, improve it relative to situations of ample water supply. As water deficits become more severe or occur at a critical stage, HI tends to decrease below the nonstress value. Terminal d r o u g h t patterns tend to reduce HI in winter cereals (Gifford, 1979; Giunta et al., 1993). In a few crops, such as sorghum (Faci and Fereres, 1980) and cotton (Orgaz et aL, 1992), mild water stress increased HI relative to irrigated controls.

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In drought situations, it is common to find a correlation between HI and yield as dry matter production is limited by the water available and the maintenance of HI becomes critical. For instance, Bolafios and Edmeades (1993) found that yield increases in maize after eight cycles of selection for drought tolerance were correlated to an increase in HI in wet and in dry environments. Improved drought tolerance was due to increased partitioning of biomass toward the developing ear during a severe drought stress that coincided with flowering rather than to a change in plant water status. Positive correlations between HI and yield have been reported for many other crops such as wheat (Loftier et al., 1985; Slafer and Andrade, 1989; Siddique et al., 1989), rice (Cook and Evans, 1983), sunflower ( Fereres et al., 1986), and chickpeas (Silim and Saxena, 1993). 2. Yield Components The harvestable part of many crops is the product of fruit number times the individual fruit weight. Fruit number and weight-the components of yield--are both affected by water deficits, particularly by its timing and its severity. If stress occurs in the early developmental stages, there could be opportunities for compensation later on, and HI and yields may not be affected. This has been shown, for example, in maize (Abrecht and Carberry, 1993), rice (Lilley and Fukai, 1994), and sorghum (Craufurd and Peacok, 1993), in which water stress in the vegetative phase did not reduce yields. On the contrary, water stress during the stages of fruit number determination or during grain filling induces the largest yield reductions. When water deficits reduce either fruit numbers or weight, there is normally some compensation between yield components. In many crops, there is more plasticity in seed number than in seed weight. For instance, Fereres et al. (1986) attributed most of the genotypic differences in the drought susceptibility of sunflower cultivars to adjustments in seed number. The ratio of seed number between a dryland and an irrigated treatment ranged from 0.39 to 0.56, whereas the grain weight ratio varied between only 0.73 and 0.77. Simane et al. (1993) studied the effect of early, mid-season, and terminal stress on durum wheat yield components. Wheat grain yield was related to the effects of early stress on kernels per spike and on duration of the grain-filling period and kernels per spike under terminal stress. When the duration of grain growth is significantly shortened by water stress, grain weight is reduced (Simane et al., 1993; Savin and Nicholas, 1996).

C. Water Conservation Strategies for Optimum Allocation We believe that one of the best strategies to obtain high yields consistently under dryland conditions is to match the patterns of crop growth and development to the patterns of water supply and use. This has largely been achieved by genetic selection in the case of winter cereals in Mediterranean-

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et

al.

type environments (Loss and Siddique, 1994), a case that is used in the subsequent discussion. Additionally, because of the possible interactions among water supply, water use, and crop growth, crop management offers options to optimally distribute the available water among the different crop stages in order to maximize yields in water-limited environments. In Section III, we emphasized that there are opportunities for increasing biomass production in the DASs. Such an increase may be mostly achieved through management practices aimed at increasing radiation interception by the crop when the soil surface is wet and the evaporative demand (radiation and VPD) is low. At those times, carbon may be acquired at a very low water cost, whereas the water not used in T is lost via E anyway. The desirable management practices that can increase biomass production include early plantings, cultivars with high early vigor, adequate starter fertilizer, and high planting densities. Such practices affect favorably both Tand TE, resulting in increased biomass production at anthesis and, hence, in increased yield potential. Whether such yield potential is realized will depend on the maintenance of HI at levels similar to those observed in nonlimiting water conditions. Most of the increases in grain yield during recent decades have been attributed to the increase in HI, which is now approaching its potential value in many crop species. In water-limited environments, further yield increases through genetically improved HI may be small (Siddique et al., 1990); thus, crop management offers the greatest potential to achieve high HI and yields in DASs. In Passioura's (1977) expression [Eq. (2)], HI cannot be considered independent of T and TE. On the one hand, higher biomass at anthesis can substantially contribute to grain yield by assimilate mobilization. On the other hand, such an increase in biomass could represent more water use during the vegetative phase, reducing the fraction available for grain filling and, consequently, affecting HI. In his analysis, Fischer (1979) proposed for wheat that, in water-limiting environments, there is a negative association between crop biomass at anthesis and water availability for grain filling, and an optimum biomass level at anthesis is proposed. Yield and HI reductions would occur when biomass exceeds such a level as a consequence of insufficient water available for grain filling (Fig. 4). This would be especially true when the differences in crop biomass at anthesis are associated to differences in preanthesis ET, as is the case of genotypes of different maturity date. However, when the higher crop biomass at anthesis is caused by higher T and TE without influencing preanthesis ET, the model in Fig. 2 does not apply. In fact, it is difficult to find experimental data showing reductions in HI and yield when radiation interception in the first crop stages and, hence, TE are improved. The few reports indicating such negative responses (Fischer and Kohn, 1966; Cantero-Martinez et al.,

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Potential sink capacity limited source Im .Jr 4~ "0

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1995) are associated with very severe terminal stress environments and long-season genotypes. We propose that practices directed to shift a higher fraction of the available water to grain filling, at the expense of restricting early crop growth, may not be suitable for improving productivity in many water-limited environments. On the contrary, the optimum strategy should be directed at increasing biomass production through m a n a g e m e n t practices that allow rapid early growth, whereas the optimum distribution of water supply between pre- and postanthesis should be determined by choosing a genotype of adequate season length. In terminal stress environments of limited water supply, early maturing cultivars should be chosen. In the very severe stress environments, flowering cannot take place soon enough, due to either genetic or environmental factors, as is the case of frost risks in winter cereals, to conserve enough water for grain filling. Only in such situations are m a n a g e m e n t practices that reduce preanthesis ET desirable. Among them, reducing planting density and low fertilization rates are the most common. When the water supply limitations are even more drastic, growing forage crops for biomass or even the use of fallow are the obvious strategies (Loomis, 1983).

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V, Integration of Responses in Dryland Agricultural Systems Crop yields in the DASs are n o t always constrained by water deficits. In fact, o t h e r limiting factors, such as nutrition, weed competition, etc., often r e d u c e yields below the potential for the a m o u n t of water available. An e x a m p l e of the i m p o r t a n c e of o t h e r a g r o n o m i c factors in limiting wheat yields in the dryland areas of south Australia was p r e s e n t e d by F r e n c h a n d Schultz (1984). Their analysis of a series of observations shown in Fig. 5 suggests that the primary yield constraint in m a n y areas may be incorrect crop m a n a g e m e n t r a t h e r than insufficient water supply. A g r o n o m y and plant b r e e d i n g are responsible for the increases in crop productivity observed over the past decades. Analyses p e r f o r m e d for wheat in several environments showed that the rate of yield increase in dryland areas has b e e n m u c h less than that observed in m o r e favorable environm e n t s (Perry a n d D ' A n t u o n o , 1989). Evidently, the slower rate of yield

Figure 5 The relation between grain yield of wheat and April-October rainfall for experimental sites and farmers paddocks. The sloping line indicates the potential yield relation. The responses to different treatments are shown by lettered lines linking points. Yield increases were obtained by the application of nitrogen (points linked by a B line), phosporus (C line), copper (D line), control of eelworms (F line), and multifactor research (J line). Yield reductions occurred because of delayed time of sowing (A line), effects of weeds (E line), and waterlogging (G line). Variation in yields in districts are shown by the H lines (from French and Schultz, 1984).

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improvement in the DASs reflects the constraint that the water limitation imposes on carbon assimilation. It also offers considerable scope for further improvement if m a n a g e m e n t is optimized. A comparison in wheat trends u n d e r dryland and irrigated conditions performed by Stanhill (1986; Fig. 6) shows very similar yield improvement rates in both situations, with irrigated yields being higher than dryland yields on the average. The outstanding feature of the data in Fig. 6 is the large fluctuations in dryland yields relative to the much more stable irrigated yield trend. Improved agronomy should focus on mitigating the impact of the very bad years and on maximizing profits in the good years. If farmers could anticipate the nature of the season, their tactical decisions would reduce yield fluctuations substantially. Among agronomic factors, nitrogen fertilization is most critical. Fast canopy development after sowing is essential to increase the T fraction in the partitioning of ET. The traditional view that nitrogen supply to dryland crops should be restricted to prevent excessive water use in the vegetative phase, so that water supply during grain filling is not exhausted, should be questioned. Three response types to N supply have been observed in

Figure 6 Trends in the level and variation of wheat yields under irrigation in Egypt (0) compared with dryland conditions in Israel (O) (from S~nhill, G., 1986. Irrigation in arid lands. Phil. Trans. R. Soc. London A 316, 261-273, Fig. 2, by the Royal Society of London).

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dryland crops; normally, the overall yield constraint in areas or years of low rainfall limits a positive response to N to moderate rates of fertilization, beyond which there is no response to increased N. When water supply conditions improve, crops exhibit a positive N response over a wide range of fertilization rates. Finally, only in areas (or years) ofvery low precipitation (less than 250 mm annual rainfall) have modest yield reductions been observed in response to increased N fertilization (i.e., Cantero-Martinez et al., 1995). It seems that, in most situations, the benefits of higher T and higher photosynthetic rates associated with increased N supply balance or outweigh the possible losses induced by the more severe water stress in the last stages of crop development caused by increased N fertilization u n d e r dryland conditions. Other management tactics, such as early plantings and use of cultivars with early vigor, should contribute to increasing Twithout having negative impacts on HI. There is an urgent need for breeding efforts in the developm e n t of cultivars that can achieve high initial growth rates u n d e r the low temperatures characteristic of seasons of low evaporative demand. To optimize agronomic practices, it is essential to develop and use analytical techniques that have some predictive value. Crop simulation models are ideal tools for risk analyses (Loomis et al., 1979; Boote et al., 1996). Model outputs are used for generating probability distributions of yield, income, or profit as a function of the environment and m a n a g e m e n t considered (Fereres et al., 1993). Cumulative probability functions are developed u n d e r several scenarios to determine the distribution that is most favorable for the objective chosen (maximum average yields, highest yield in the drier years, lowest risk, etc.). Simulation models can also be a valuable tool for matching genotypes to environments (Boote et al., 1996) and for evaluating m a n a g e m e n t strategies to improve productivity in water-limiting conditions (Muchow and Bellamy, 1991; Villalobos et al., 1994). As an example of an application to design an optimal cropping sequence, Fereres et al. (1993) compared three crop sequences using wheat and sunflower in a Mediterranean climate of about 600 mm annual rainfall. U n d e r such conditions, wheat does not use all the winter rainfall and there is substantial residual moisture in the subsoil at harvest. On the contrary, continuous sunflower cropping, a spring crop, can exhaust all available water well before harvest and even fails in the dry years. The current wheat-sunflower (W-S) rotation was compared in a simulation to continuous wheat (W), continuous sunflower (S), and a wheat-wheat-sunflower ( W - W - S ) rotation (Fereres et al., 1993). The probability distributions for each case showed that the W - W - S sequence had higher average wheat yields than in the W - S rotation and also had higher sunflower yields in 9 of 10 years, thus it is apparently more sustainable than the W - S sequence used in the area.

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M a n a g e m e n t tactics, such as p l a n t i n g dates, fertilization rates a n d timing, a n d cultivars o f d i f f e r e n t season length, can be e v a l u a t e d in l o n g - t e r m scenarios to select the best strategy. A n o t h e r r e l a t e d a p p l i c a t i o n o f m o d e l s is their use for tactical variations o f the selected strategies at the start o f the season or within a season. This is very useful to fully e x p l o i t the r e s o u r c e s available w h e n the year c o n d i t i o n s are m o r e favorable t h a n o n the average or to avoid c r o p failure in the very dryyears. Such applications are b e c o m i n g realistic a n d feasible as w e a t h e r p r e d i c t i o n s are i m p r o v e d . For instance, H a m m e r et al. (1996) e v a l u a t e d the value o f seasonal forecasts b a s e d o n the SOI for tactical m a n a g e m e n t decisions in w h e a t p r o d u c t i o n in n o r t h e a s t e r n Australia. T h e y s h o w e d that, by using forecasts to m a k e decisions o n N fertilizer a n d cultivar maturity, profits i n c r e a s e d by 20% a n d the risk o f a loss d e c r e a s e d by 35%. In this case, a c r o p s i m u l a t i o n m o d e l c o m b i n e d with seasonal forecasts illustrates the feasibility o f u s i n g such tools for i m p r o v i n g the agricultural productivity o f that area. B o t h seasonal w e a t h e r forecasts a n d s i m u l a t i o n m o d e l s n e e d substantial i m p r o v e m e n t s to increase the precision a n d accuracy o f t h e i r predictions. R e s e a r c h efforts are essential for such i m p r o v e m e n t s if these n e w tools are to play an i m p o r t a n t role in the m a n a g e m e n t o f DASs in the future.

VI. Conclusions Productivity o f DASs is low a n d all efforts to i m p r o v e it have h a d only m o d e s t success w h e n c o m p a r e d to the i m p r o v e m e n t o f yield in the agricultural systems in w h i c h water is n o t so limiting. In the s h o r t term, we believe t h a t strategic a n d tactical m o d i f i c a t i o n s o f c r o p m a n a g e m e n t offer scope for i n c r e a s i n g the productivity in water-limited e n v i r o n m e n t s .

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Austin, R. B., Morgan, C. L., Ford, M. A., and Blackwell, R. D. (1980). Contributions to grain yield from pre-anthesis assimilation in tall and dwarf barley phenotypes in two contrasting seasons. Ann. Bot. 45, 309-319. Bidinger, F., Musgrave, R. B., and Fischer, R. A. (1977). Contribution of stored pre-anthesis assimilate to grain yield in wheat and barley. Nature 270, 431-433. Blum, A., and Arkin, G. F. (1984). Sorghum root growth and water use as affected by water supply and growth duration. Field Crops Res. 9, 131-138. Blum, A., Poiarkova, H., Golan, G., and Mayer, J. (1983). Chemical dessication of wheat plants as a simulator of post-anthesis stress. I. Effects on translocation and kernel growth. Field Crops Res. 6, 51-58. Bolafios, J., and Edmeades, G. O. (1993). Eight cycles of selection for drought tolerance in lowland tropical maize. I. Responses in grain yield, biomass, and radiation utilization. Field Crops Res. 31, 233-252. Boote, K. J., Jones, J. w., and Picketing, N. B. (1996). Potential uses and limitations of crop models. Agron. J. 88, 704-716. Brouwer, R. (1983). Functional equilibrium: Sense or nonsense? Netherlands J. Agric. Sci. 31,335-348. Cantero-Martinez, C., Villar, J. M., Romagosa, I., and Fereres, E. (1995). Nitrogen fertilization of barley under semi-arid rainfed conditions. Eur. J. Agron. 4, 309-316. Cary, J. W. (1966). Soil moisture transport due to thermal gradients: Practical aspects. Soil Sci. Soc. Am. Proc. 30, 428-433. Clewett, J. F., Howden, S. M., McKeon, G. M., and Rose, C. W. (1991). Optimising farm dam irrigation in response to climatic risk. In "Climatic Risk in Crop Production: Models and Management for the Semiarid Tropics and Subtropics" (R. C. Muchow and J. A. Bellamy, eds.), pp. 307-328. CAB International, Wallingford, UK. Connor, D.J., and Jones, T. R. (1985). Response of sunflower to strategies of irrigation. II. Morphological and physiological responses to water stress. Field Crops Res. 12, 91-103. Constable, G. A., and Hearn, A. B. (1978). Agronomic and physiological responses of soybean and sorghum crops to water deficits. Aust. J. Plant Physiol. 5, 159-167. Cook, M. G., and Evans, L. T. (1983). Some physiological aspects of the domestication and improvement of rice (Oryza spp.). Field Crops Res. 6, 219-238. Cooper, P.J., Gregory, P.J., Tully, D., and Harris, H. (1987). Improving water use efficiency of annual crops in the rainfed farming systems of west Asia and north Africa. Exp. Agric. 23, 113-158. Cooper, P.J.M. (1983). Crop management in rainfed agriculture with special reference to water use efficiency. Proc. 17th Colloquium Int. Potash Inst., Bern, Switzerland, pp. 63-79. Craufurd, P. Q., and Peacock, J. M. (1993). Effect of heat and drought stress on sorghum (Sorghum bicolor). 2. Grain yield. Exp. Agric. 29, 77-86. Day, W., Lawlor, D. W., and Day, A. T. (1987). The effect of drought on barley yield and water use in two contrasting years. Irrig. Sci. 8, 115-130. Dregne, H. E. (1982). Dryland soil resources. Science and Technology Agriculture Report. Agency for International Development, Washington, DC. Ehlers, W., Hamblin, A. P., Tennant, D., and van der Ploeg, R. R. (1991). Root system parameters determining water uptake of field crops. Irrig. Sci. 12, 115-124. Faci, J. M., and Fereres, E. (1980). Responses of grain sorghum to variable water supply under two irrigation frequencies. Irrig. Sci. 1, 149-159. Farquhar, G. D., and Richards, R. A. (1984). Isotopic composition of plant carbon correlates with water-use efficiency of wheat genotypes. Aust. J. Plant Physiol. 11,539-552. Farquhar, G. D., O'Leary, M. H., and Berry, J. A. (1982). On the relationship between carbon isotope discrimination and intercellular carbon dioxide concentration in leaves. Aust. J. Plant Physiol. 9, 121-137.

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Fereres, E. (1987). Responses to water deficits in relation to breeding for drought resistance. In "Drought Tolerance in Winter Cereals" (P. Srivastava, E. Porceddu, E. Acevedo, and S. Varma, eds.), Proceedings of an International Workshop, ICARDA, Capri, Italy, pp. 263-273. Wiley, Chichester, UK. Fereres, E., Gimenez, C., and Fernandez,J. M. (1986). Genetic variability in sunflower cultivars under drought. I. Yield relationships. Aust. J. Agric. Res. 37, 573-582. Fereres, E., Orgaz, F., and Villalobos, F.J. (1993). Water use efficiency in sustainable agricultural systems. In "International Crop Science. I" (D. R. Buxton, R. Shibles, R. A. Forsberg, B. L. Blad, K. H. Asay, G. M. Paulsen, and R. F. Wilson, eds.), pp. 83-89. CSSA, Madison, WI. Fischer, R. A. (1979). Growth and water limitation to dryland wheat yield in Australia: A physiological framework. J. Aust. Inst. Agric. Sci. 45, 83-94. Fischer, R. A. (1981). Optimizing the use of water and nitrogen through breeding of crops. Plant Soil 58, 249-278. Fischer, R. A. (1987). Responses of soil and crop water relations to tillage. In "Tillage" (P. S. Cornish and J. E. Pratley, eds.), pp. 194-221. Inkata Press, Melbourne, Australia. Fischer, R. A., and Kohn, G. D. (1966). The relationship of grain yield to vegetative growth and post-flowering leaf area in the wheat crop under conditions of limited soil moisture. Aust. J. Agric. Res. 17, 281-295. Fischer, R. A., and Turner, N. C. (1978). Plant productivity in the arid and semiarid zones. Annu. Rev. Plant Physiol. 29, 277-317. French, R. J., and Schultz, J. E. (1984). Water use efficiency of wheat in a mediterraneantype environment. II. Some limitations to efficiency. Aust. J. Agric. Res. 35, 765-775. Gallagher, J. N., Biscoe, P. V., and Scott, R. K. (1975). Barley and its environment. V. Stability of grain weight. J. Appl. Ecol. 12, 319-336. Gen, S., Penning de Vries, F. W. T., and Supit, I. (1986). A simple method for generating daily rainfall data. Agric. For. Meteorol. 36, 363-376. Gifford, R. M. (1979). Growth and yield of CO2-enriched wheat under water-limited conditions. Aust. J. Plant Physiol. 6, 367-378. Gimenez, C., and Fereres, E. (1986). Genetic variability in sunflower cultivars under drought. II. Growth and water relations. Aust. J. Agric. Res. 37, 583-597. Gimeno, V., Fernandez, J. M., and Fereres, E. (1989). Winter plantings as a means of drought escape in sunflower. Field Crops Res. 22, 307-316. Giunta, F., Motzo, R., and Deidda, M. (1993). Effect of drought on yield and yield components of durum-wheat and triticale in a Mediterranean environment. Field Crops Res. 33, 399-409. Gonzalez, P., Fereres, E., Giraldez, J. V., Martin, I., Garcia, M., Gil, J., and Agfiera, J. (1988). Non tillage dry farming in heavy clay soils under Mediterranean climate. Proc. l l t h Int. Conf. of the Int. Soil Tillage Res. Organization, Edinburgh, Scotland, Vol. 2, pp. 661-666. Gregory, P.J. (1994). Root growth and activity. In "Physiology and Determination of Crop Yield" (K. J. Boote, J. M. Bennett, T. R. Sinclair, and G. M. Paulsen, eds.), pp. 65-93. ASA, CSSA, SSSA, Madison, WI. Gregory, P.J., Shepherd, K. D., and Cooper, P. J. M. (1984). Effects of fertilizer on root growth and water use of barley in Northern Syria. J. Agric. Sci. Cambridge 103, 429-438. Hall, A. E., Ismail, A. M., and Menendez, C. (1993). Implications for plant breeding of genotypic differences in water use efficiency, carbon isotope discrimination and gas exchange. In "Stable Isotopes and Plant Carbon-Water Relations" (J. R. Ehleringer, A. E. Hall, and G. D. Farquhar, eds.), pp. 349-370. Academic Press, San Diego. Hamblin, A., and Tennant, D. (1987). Root length density and water uptake in cereals and grain legumes: How well are they correlated? Aust. J. Agric. Res. 38, 513-527. Hammer, G. L., and Muchow, R. C. (1991 ). Quantifying climatic risk to sorghum in Australia's semiarid tropics and subtropics: Model development and simulation. In "Climatic Risk in Crop Production: Models and Management for the Semiarids Tropics and Subtropics" (R. C. Muchow andJ. A. Bellamy, eds.), pp. 205-232. CAB International, Wallingford, UK.

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5 Nitrogen as a Limiting Factor: Crop Acquisition of Ammonium and Nitrate

Arnold J. Bloom

I. Importance of Nitrogen Acquisition Most natural and agricultural ecosystems show a dramatic increase in productivity when they receive nitrogen fertilizer (van Keulen and van Heemst, 1982) and, thus, nitrogen is considered to be a major factor that limits plant growth. Plants have evolved diverse mechanisms to capture nitrogen, including symbiotic relationships with nitrogen-fixing bacteria or mycorrhizal fungi, insect carnivory, root absorption of amino acids from organic soils, and leaf absorption of nitrogen from atmospheric deposition or foliar application. Despite an inherent interest in such mechanisms, their contributions to the nitrogen economy of crops are usually minor [nitrogen-fixing bacteria, Peoples and Craswell (1992); mycorrhizal fungi, Marschner (1995); insect carnivory, Dixon et aL (1980); amino acids, Chapin et al. (1993); foliar absorption, Nicoulaud and Bloom (1996)]. For crops, nitrogen acquisition primarily involves root absorption of ammonium (NH~) or nitrate (NO~) from the soil solution and the subsequent assimilation of these ions into amino acids within roots and shoots (Bloom, 1994). This chapter describes the physiological processes through which crops absorb and assimilate NH~ and NOg. These processes are among the most energy intensive in life and, thus, determine not only the nitrogen budgets of plants but also their carbon balance. Crop performancembe it yield, fertilizer efficiency, or susceptibility to biological or environmental stressmgenerally hinges on NH~ and NO~ acquisition. The chapter takes Ecology in Agriculture

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a n " epidermis-in" approach, focusing on nitrogen acquisition from absorption at the root surface to the assimilation into organic nitrogen within tissues. The chapter by Robertson (Chapter 10, this volume) provides a more "epidermis-out" perspective in that it considers nitrogen cycling in ecosystems and soil nitrogen transformations. The first half of this chapter treats NH] and NO~ separately. For each ion, I discuss (i) its importance to crops, (ii) the characteristics of its root absorption, (iii) its assimilation into amino acids, and (iv) the internal and external factors that regulate its acquisition. I emphasize root absorption at micromolar concentrations because NH] or NO~ levels in the rhizos p h e r e - - t h e environment immediately surrounding a root--usually fall within this range (Bloom, 1994). In the second half of the chapter, I contrast NH] and NO~ as nitrogen sources and describe the physiological and developmental consequences of using one form over the other. For additional information on these topics, I refer the reader to the recent reviews of Hoff et al. (1994), Imsande and Touraine (1994), Lynch (1995), and, particularly, Oaks (1994), Glass and Siddiqi (1995), and Marschner (1995).

II. Physiology of Root Ammonium Acquisition A. Importance of Ammonium as a Nitrogen Source Ammonium is the preferred inorganic source of nitrogen for microorganisms and many plants (Kleiner 1981, 1985; Dortch, 1990; Huppe and Turpin, 1994). The availability of NH] from soils generally shows much less variation both seasonally and spatially than the availability of other nitrogen forms, particularly NO~. As a consequence, NH] may be the major nitrogen form available at certain times and places. However, plant NH] acquisition has received relatively litde attention. This lack of research activity stems from two common misconceptions: that passive diffusion of NH3 through biological membranes is predominately responsible for NH] absorption (Henderson, 1971; Pitts, 1972) and that higher plants grow better with NOg as the sole nitrogen source (Haynes, 1986; Lewis, 1986). Root NH] absorption can proceed via NH3 diffusion through the membranes of root cells because NH~ is highly membrane permeable and NH] interconverts rapidly with NH3. The following results, however, argue that root NH] influx depends more on carrier-mediated NH] transport than on NH~ diffusion:

1. Gradients of NH3 between the rhizosphere and cytoplasm usually oppose passive NH3 diffusion into root cells. In agronomic soils, the solution near roots normally has NH] concentrations between 10 and 50 /zM (about 0.03-

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0.30/~g N H ~ - N g-1 dry soil; Novoa a n d Loomis, 1981; Haynes, 1986) a n d a p H below 6 (e.g., Jackson a n d Bloom, 1990; Lee a n d Ratcliffe, 1991). T h e pK~ of the reaction NH~ ~ NHa + H + is 9.25. Consequently, rhizosphere NH3 levels should vary between 0.006 a n d 0.03/~M. By contrast, the root cytoplasm maintains a p H of between 7.0 a n d 7.8 a n d contains from 3 to 438/~MNH~ (Roberts a n d Pang, 1992), from 3 to 12 m M N H ~ (Lee a n d Ratcliffe, 1991), or m o r e than 30 m M N H ~ (Wang et al., 1993; Kronzucker et al., 1995), d e p e n d i n g on methodology; a calculation based on the pK~ indicates that cytoplasmic NHa should range from 0.07 to 700 ~M. Thus, u n d e r most conditions, the NHa c o n c e n t r a t i o n gradient should oppose the inward diffusion of NHa across the root cell m e m b r a n e (Kronzucker et al., 1995). 2. Exposure to NH~ depolarizes the plasmalemma. W h e n a plant cell is first exposed to NH~, the electrical potential within the cell initially shifts to a m o r e positive value (cf Section II,B). Diffusion of neutral molecules such as NH3 into a cell would not alter this potential, whereas unidirectional influx of cations such as NH~ would have the observed effect. 3. Root NH~ influx depends on energy metabolism. About 2 ATP are e x p e n d e d p e r NH~ absorbed (Fig. 1; Bloom et al., 1992). Metabolic inhibitors, such as KCN or arsenate (Sasakawa a n d Yamamoto, 1978), hypoxia (Sasakawa

Figure I Root CO2 evolution (hatched bars), 02 consumption (open bars), and respiratory quotient (RQ; solid bars) in two genotypes of Hordeum vulgare L. cv. Steptoe under different nitrogen nutrition. (A) Wild-type plants and (B) a nada;nag7w mutant that is deficient in both NADH nitrate reductase and NAD(P)H nitrate reductase were exposed to media first devoid of nitrogen, then containing 50/xM NH], and last containing 50/xM NO~. Fluxes are expressed per gram dry weight of root. Shown are the mean _+ SE (n = 6-23). The wild type had lower root 02 consumption when shifted from NH] nutrition to NO~ nutrition (A); the nada;naCTw mutant, the genotype that had diminished root NO~ assimilation, showed no change in 02 consumption when shifted from NH] nutrition to NO~ nutrition (B). Thus, the diminished 02 consumption reflects the respiratory cost of NO~ assimilation. (Bloom et al., 1992).

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and Yamamoto, 1978; Koch and Bloom, 1989), and low temperatures (Bloom et al., 1993), immediately and severely diminish NH] absorption. A physical process such as NHs diffusion would exhibit less sensitivity to these factors. 4. Root NH] absorption follows saturation kinetics. Over the range of concentrations normally found in the rhizosphere, net NH] uptake approximates Michaelis-Menten kinetics (Fig. 2; Bloom, 1994). NH~ influx saturates at a r o u n d 2 0 0 / z M N H ] (Bloom, 1985; Smart and Bloom, 1988) and does not vary directly with root NH~ content (Morgan and Jackson, 1988a). These observations support the contention that NH] influx is carrier mediated; NH~ diffusion or channel-mediated NH] influx would display a more linear response to external concentration and would respond directly to root NH] content. The second s u p p o s i t i o n m t h a t plants prefer NO~mis based on n u m e r o u s solution culture experiments in which unrealistically high levels of NH] were applied or pH control was inadequate (Bloom, 1988, 1994). Nutrient solutions typically contain more than 2 m M NH], whereas most ~plants require less than 2 0 / z M NH~ to sustain rapid growth (Ingestad and Agren, 1988; Smart and Bloom, 1993). High NH] levels in a nutrient solution stimulate high root absorption rates, but the low light levels found in most controlled environment chambers permit only low NH] assimilation rates: With high absorption and low assimilation, free NH] accumulates in plant tissues and becomes toxic. A m m o n i u m toxicity probably derives from dissi-

Figure 2 Kineticsof (A) NH~ or (B) NO; absorption for Lycopersiconesculentum grown under low levels of NH~ and NO~. Absorption was estimated either by the rate of accumulation of 15N into plants exposed for 10 min to solutions containing predominantly [15N]NH~ or [15N]NO~ (15NH~or 15NOginflux; closed symbols) or by the rate of depletion of NH~ or NOg from a nutrient solution after a single pass through a root cuvette (net NH~ or NO~ uptake; open symbols). The difference between the two measures provides an estimate of effiux. (Smart and Bloom, 1988; Kosola and Bloom, 1994, 1996).

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pation of the t r a n s m e m b r a n e p r o t o n gradients r e q u i r e d b o t h for photosynthetic a n d respiratory e l e c t r o n t r a n s p o r t a n d for a c c u m u l a t i n g metabolites in the vacuole (Fig. 3). Moreover, without a d e q u a t e p H control, NH]-based n u t r i e n t solutions quickly b e c o m e acidic as roots balance NH] a b s o r p t i o n a n d assimilation t h r o u g h the release of H + into the r h i z o s p h e r e (cf Section II,B). I n c r e a s e d acidity inhibits n e t NH] uptake (Lycklama, 1963) so that the s t u n t e d growth often observed with NH] n u t r i t i o n may result f r o m n i t r o g e n deficiencies at low pH, n o t f r o m toxic effects (Tolley-Henry a n d Raper, 1986). If the e x p e r i m e n t a l artifacts of NH~ toxicity a n d m e d i a acidity are avoided, most plants grow faster w h e n they have access to b o t h NH~ a n d NO~ (Fig. 4; Section IV,A; Cox a n d Reisenauer, 1973; G a n m o r e N e u m a n n a n d Kafkafi, 1980; Haynes, 1986; Bloom, 1988; S c h o r t e m e y e r et al., 1993; Smart a n d Bloom, 1993; Marschner, 1995).

B. Ammonium Absorption T h e a b s o r p t i o n of NH~ f r o m the r o o t / s o i l interface, as o u t l i n e d previously, involves a carrier-mediated m e m b r a n e t r a n s p o r t system. T h e characteristics of this system largely d e t e r m i n e the capacity of a plant to obtain NH~ f r o m its e n v i r o n m e n t and, thus, the fertilizer efficiency of a crop. T h e following sections discuss plant m e m b r a n e t r a n s p o r t systems for NH~, their d e p e n d e n c e o n c o u n t e r i o n s to balance the inward m o v e m e n t of positive charges, a n d their specificity for NH~.

OH"

OH"

OH" |

^.. un

H,~'~~~Lume

n, Intermembrane, / H+ _.,,__. ~ " H* or Vacuole -,NH 3-~.~= | "" ~ NH3 + H § ~ NH4 + Stroma, NH4 § + OH" OH" / Matrix, or Cytoplasm OH" [ H* H* [ H. H* H + H+ OH"

3

OH"

/

A schematic showing how NH~ toxicity may result from the dissipation of pH Figure gradients. Here a pH gradient across a biological membrane is depicted where the pH is higher on the left side of the membrane. The left side represents the stroma, matrix, or cytoplasm; the right side represents the lumen, intermembrane space, or vacuole; and the membrane represents the thylakoid, inner mitochondrial, or tonoplast membrane for a chloroplast, mitochondria, or root cell, respectively. (1) IfNH~ is present at sufficient concentrations, it will react with OH- on the left side of the membrane to produce NH3. (2) This NHa is membrane permeable and will diffuse across the membrane along its concentration gradient. (3) On the right side of the membrane, the NH3 will react with H + to form NH~. The net result is that both the OH- concentration on the left side and the H + concentration the right side have been diminished, that is, the pH gradient has been dissipated.

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Figure 4 Growth of tomato (Lycopersicon esculentum Mill. cv. T5) when nitrogen was supplied as 20/zM NH4C1 (A), 50/zM KNO~ (V-l), 100/zMNH4C1 (A), 200/zM KNO~ (m), or 20/~M NH4C1 and 50/zM KNO3 (~). Log dry weight of plant (mean +_ SE) is plotted against days after transplanting to the different nutrient regimes. Root temperature was 20~ Small error bars are incorporated into the symbols. The lower concentrations of NH~ and NO~ were selected because they are similar to the apparent K~'s for absorption of each ion; the higher concentrations represented levels at which absorption of each ion saturates. The nutrient concentrations were maintained to within 20% of the designated concentration and pH was controlled at pH 6.0 + 0.2. (Smart & Bloom 1993).

I. Membrane Transport The carrier-mediated NH] transport system that predominates at normal rhizosphere concentrations is thought to be an u n i p o r t - - a system that transports NH] through a membrane without requiring the movement of another ion (Ullrich, 1987; Glass, 1988). Evidence for an uniport is based on the strong depolarization of the plasmalemma (i.e., a rapid increase in the electrical potential of a cell) that occurs when internodal cells of Chara corallina (Smith and Walker, 1978), rhizoid cells of Riccia fluitans (Bertl et al., 1984), frond epidermal cells of Lemna gibba (Ullrich et al., 1984), coleoptiles of Avena sativa (Higinbotham et al., 1964), and tomato or barley roots (Ayling, 1993) are first exposed to NH]. 2. Counterions Although NH] membrane transport does not involve the immediate movement of another ion, a cell cannot sustain an inward movement of positive charges such as NH] without a counterion flow to restore electroneutrality. Some cations must exit the cell a n d / o r some anions must enter the cell so that the cell membrane potential returns to a physiological favorable level. During longer exposure to NH~, (i) cells assimilate the NH~ they have absorbed, (ii) assimilation of NH] to a monocarboxylmonoamino acid generates an H + that lowers cytoplasmic pH (Allen, 1988), (iii) both

5. Nitrogen as a Limiting Factor

151

the pH shift and membrane depolarization stimulate plasmalemma H § ATPases to pump H + out of the cell (Hendrich and Schroeder, 1989; Kurkdjian and Guern, 1989; Serrano, 1989), and (iv) increased acidity outside the cell stimulates anion influx (Tyerman, 1992). This H § efflux and anion influx balance NH~ influx (Raven and Smith, 1976), and the cell recovers to its initial membrane potential. Therefore, NH~-induced depolarizations are transient (Smith and Walker, 1978; Bertl et al., 1984; Ullrich et aL, 1984; Ayling, 1993). This scenario for root NH~ absorption explains several phenomena. Many of the effects ascribed to NH~ nutrition, such as diminished absorption of K+, CI-, NOL and H2PO4 during short-term experiments, probably derive from NH~-induced membrane depolarizations and, thus, are transient (Rufty et al., 1982; Ullrich et al., 1984; Bloom and Finazzo, 1986; Tyerman et al., 1986; Vale etal., 1988). An alkaline rhizosphere facilitates H § efflux so that the pH optimum of NH~ absorption is high, above pH 8 (Lycklama, 1963; Munn and Jackson, 1978; Marcus-Wyner, 1983). The effectiveness of an anion as a counterion for NH~ absorption depends not only on its concentration but also on its mobility through a membrane. Mobilities of common anions decrease in the order CI-, NOL PO43-, and SO24-; correspondingly, NH~ absorption from NH4C1 is faster than that from NH4NO~ or NH4H2PO4, which, in turn, is faster than that from (NH4)2SO4 (Lycklama, 1963). 3. Specificity The NH~ transport system that predominates under normal rhizosphere conditions is highly specific for NH~. For example, CH~NH~ serves as a NH~ transport analog in bacteria and fungi (Kleiner, 1981, 1985) and coelutes with NH + from cation-exchange columns (Kosola and Bloom, 1994); nonetheless, root affinity for NH~ exceeds that for CH3NH; by nearly an order of magnitude (Deane-Drummond, 1986; Kosola and Bloom, 1994). Potassium is also similar to N H ~ N H ~ competes directly with K+ for root K+ absorption (Rufty et al., 1982; Bloom and Finazzo, 1986; Vale et al., 1988; Smart and Bloom, 1991), and NH~ and K+ bind equally to soil particles (Loomis and Conner, 1 9 9 2 ) ~ b u t K+ has a negligible effect on root NH~ absorption (Scherer et al., 1984; Bloom and Finazzo, 1986; Smart and Bloom, 1988; Bloom and Sukrapanna, 1990). Crops must absorb nearly twice as much nitrogen as potassium from soils that contain a least an order of magnitude more K+ than NH~ (Epstein, 1972); clearly, a root transport system with high specificity for NH~ is critical to crop performance.

C. Ammonium Assimilation To avoid NH~ toxicity, roots assimilate NH~ into amino acids quickly after it is absorbed. This process is carbon limited both because the assimilation reactions are energy intensive and account for about 15% of root respiration

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(Figs. 1 and 5; Bloom et al., 1992) and because amino acid synthesis requires carbon skeletons, usually c~-ketoglutarate generated through dark carbon fixation (Cramer et al., 1993). As a consequence, NH] assimilation is central to the nitrogen and carbon budgets of roots. Assimilation of NH] in roots occurs via a cycle involving the sequential action of glutamine synthetase (GS) and glutamate synthase (GOGAT) (Oaks and Hirel, 1985; Emes and Bowsher, 1991; Amancio and Santos, 1992). The predominant form of GS in roots is cytosolic (Suzuki et al., 1981; Fentem et al., 1983; Tingey et al., 1987), but another form has been found in plastids (V~zina et al., 1989). Probably, the cytosolic form produces glutamine for export, whereas the plastid form is the one that functions primarily for N metabolism in the root itself (Oaks, 1994). Roots may have two forms of GOGAT, one that depends on a ferredoxin-like protein as an electron donor (Suzuki et al., 1982; Suzuki and Gadal, 1984) and another that can use NADH or NADPH (Suzuki and Gadal, 1984; Anderson et al., 1989); both forms are found in plastids (Oaks and Hirel, 1985; Bowsher et al., 1993). Altering the properties of these enzymes through genetic engineering has yielded significant changes in crop growth (Lam et al., 1996), and future cultivars are likely to be modified in these reactions. D. Regulation of Ammonimn Acquisition To meet the nitrogen demands of growth but avoid toxic NH~ accumulations requires precise regulation of root NH~ absorption and assimilation. Net NH~ uptake, the difference between influx and efflux, changes quickly with plant nitrogen status; it decreases under high nitrogen nutrition and increases during nitrogen deprivation (Lycklama, 1963; Lee and Rudge, 1986; Morgan and Jackson, 1988a,b, 1989). Because under normal rhizosphere conditions root NH~ efflux is a small fraction of influx (Fig. 2; Kosola and Bloom, 1994), net NH~ uptake is probably regulated through control of influx and assimilation. Rhizosphere NH~ may serve as a positive effector and root glutamine as a negative effector of root NH~ influx (Feng et al., 1994). Exposure to

assimilation 3 ATP

7 ATP

2 ATP

NR

NiR

GSIGOGAT

NO3- ---~ NO2- ---~ NH4§ ---~ Glutamate 1 ATP

absorption

1 ATP

Figure 5 Energyrequirements of NH~ and NO; absorption and assimilation. As indicated, approximately 1 ATP is required for roots to absorb either NH~or NO; from the soil solution; approximately 10 ATP is required to convert NO; to NH~ and 2 ATP to convert NH~ to glutamate. NR, nitrate reductase; NiR, nitrite reductase; and GS/GOGAT, glutamine synthetase/glutamate synthase. (Bloom et al., 1992).

5. Nitrogen as a Limiting Factor

153

rhizosphere NH] increases NH] influx in nitrogen-limited plants (Goyal and Huffaker, 1986; Morgan and Jackson, 1988a), but this results more from a relief of nitrogen deficiency than from an NH]-specific induction of NH] absorption (Nicoulaud and Bloom, 1994). Glutamine represses NH] influx in several microorganisms (Kleiner, 1981, 1985; Syrett and Peplinska, 1988). Data on maize indicate a positive correlation between NH] influx and the ratio of NH] to glutamine in the root (Lee et al., 1992; Gojon et al., 1993). Nonetheless, tissue levels of NH] and glutamine can vary independently of root NH] influx (Glass and Siddiqi, 1995). Information on the control of root NH~ assimilation is meager (Oaks and Hirel, 1985). Assimilation is an energy-intensive process (cf, Section II,C) that varies with root carbohydrate levels (Reisenauer, 1978; Haynes, 1986; Bloom and Caldwell, 1988). Root carbohydrate levels are inversely correlated to the nitrogen status of a plant (Brouwer, 1967; Brouwer and DeWit, 1969; Talouizte et al., 1984). Therefore, root carbohydrate levels may serve as a positive effector of NH] assimilation.

III. Physiology of Root Nitrate Acquisition A. Importance of Nitrate as a Nitrogen Source The availability of NO~ in well-aerated, temperate, agricultural soils typically exceeds that of NH~ by an order of magnitude. In such soils, microbes rapidly convert organic nitrogen to NO~. This NO~ moves relatively freely through the soil (Nye and Tinker, 1977) because NOL as an anion, does not bind to the soil cation-exchange capacity and because all NO~ salts are highly soluble. Plants can store relatively high concentrations of NO~ in their tissues without toxic effect (Lorenz, 1978; Goyal and Huffaker, 1984). For these reasons, most crops in temperate zones rely on NO~ to meet a major portion of their nitrogen requirements (Haynes, 1986) and to serve as a metabolically benign osmoticum (Hanson and Hitz, 1983). This does not mean that crops depend on NO~ as their sole nitrogen source, just that in temperate agroecosystems, NO~ is often the major nitrogen source. B. Nitrate Absorption Root absorption of NO~ from the soil solution depends on at least two distinct transport mechanisms: one system (mechanism I or high affinity transport system) predominates at lower concentrations (1 mM) and appears to be a more general anion channel (Glass and Siddiqi, 1995). Models of nutrient depletion from the soil around roots (Nye and Tinker, 1977) and the kinetics parameters of root NO~ absorption (Crowley, 1975)

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Arnold J. Bloom

indicate that NO~ concentrations near root surfaces are generally below 1 mM. Consequently, the discussion here will focus on the mechanism I system. 1. Membrane Transport Thermodynamic conditions do not favor passive NO~ movement across the plasmalemma into the cytoplasm of root cells. The cytoplasm maintains a negative potential with respect to its exterior ( - 100 to - 2 5 0 mV; Ullrich, 1991) and contains a higher NO] concentration (5-30 mM; Lee and Clarkson, 1986; Zhen et al., 1991; King et al., 1992; Walker et al., 1995) than the rhizosphere (0.1-1.0 mM; Novoa and Loomis, 1981); thus, both electrical and chemical potentials oppose NO~ influx. To transport NO~ against these potentials requires expenditure of metabolic energy (Bloom and Caldwell, 1988; Glass et al., 1990; Bloom et al., 1992) in a process that involves cotransport ofH + (Ullrich, 1992; King et al., 1992). Plants commonly employ a H + cotransport mechanism for transport of ions or molecules against electrical and chemical potential gradients (Serrano, 1989). The plasmalemma possesses H+-translocating ATPases that use the energy released through hydrolysis of ATP to transport H + out of the cytoplasm, thereby creating an electrical potential and a proton gradient across the plasmalemma. These favorable electrical and chemical potentials--the so-called protonmotive forcemcan drive thermodynamically unfavorable transport of ions or molecules by coupling the energetically downhill movement of H + to the uphill transport of the other species. Evidence for cotransport of H + and NOg across the plasmalemma has been based on the response of the membrane potential to varying external NO~ concentrations. If H + diffusion drives NO~ transport and H + :NO~ stoichiometry is greater than 1, then raising external NO] concentration and, presumably, increasing NO; influx should produce a transient depolarization. In fronds of the aquatic higher plant Lemna gibba, exposure to NO~ caused a transient depolarization that appeared to be associated with NO~ influx because both increased in a similar manner with time after first exposure to NO~ and with increasing [NO~] ext (Ullrich and Novacky, 1981). Intact barley roots showed a transient depolarization upon first exposure to NO~ that increased with [ N 0 3 ] ext (Glass et al., 1992). These data support that NO~ influx entails the cotransport of 2 H § 2. Counterions Root NO~ absorption is sensitive to the availability of cations (Minotti et al., 1968) but not to species--with the exception of NH~mof cation (Lycklama, 1963). Addition of nontoxic levels of NH~ may either inhibit (Bloom and Finazzo, 1986; Glass and Siddiqi, 1995) or stimulate (Fig. 6; Bloom and Finazzo, 1986; Smart and Bloom, 1988) NO? absorption. The pH optimum for root NO~ absorption is generally below pH 6 (Munn and Jackson, 1978; Marcus-Wyner, 1983; Vessey et al., 1990), presumably because of the increased availability of H + for cotransport.

5. Nitrogen as a Limiting Factor "7" e-

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6 Concentration dependence of net NO3 uptake when NOa was supplied as NH4NOs (O) or as KNO3 (A); shown are the mean _+ SE with small error bars incorporated into the symbols. (A) Data for Hordeum vulgare L. Steptoe, a common barley cultivar in Oregon and Washington. Notice that full-scale for net NOg uptake is 1.25 /zmol gDw-1 root min -1. (B) Data for Lycopersicon esculentum Mill. T5, a fresh-market tomato cultivar grown in California. Notice that full-scale for net NOg uptake is 5.0/zmol gDw-1 root min -1. (Bloom, 1994). Figure

3. Specificity The carrier-mediated NOg transport system that operates at n o r m a l rhizosphere concentrations is highly specific for NOg (Siddiqi et al., 1990). Chlorate (ClOg), an anion that coelutes with NOg from ionexchange columns and is readily r e d u c e d by nitrate reductase, does not compete with NO~ for this transport system (Siddiqi et al., 1992; Kosola and Bloom, 1996). In addition, this NO~ system is relatively insensitive to C1- and SO 2-, two anions that may be present in the soil solution at high levels (Glass and Siddiqi, 1985; D e a n e - D r u m m o n d , 1986; Bloom and Finazzo, 1986). Such selectivity permits crops to absorb NOg with minimal interference from o t h e r soil constituents.

C. Nitrate Assimilation

Assimilation of NO~ into NH~ involves the stepwise reduction of NO~ to NO2 via nitrate reductase (NR) and NO2 to NH~ via nitrite reductase (NiR) (Fig. 5). NR is generally believed to be cytosolic (Vaughn and Campbell, 1988; Oaks, 1994; but see Ward et al., 1989; Meyerhoff et al., 1994), whereas NiR is located in the stroma of chloroplasts or within plastids in roots (Oaks and Long, 1992). These reactions are energy intensive, requiting the transfer of two electrons in the form of N A D ( P ) H for NR and six electrons from r e d u c e d ferredoxin or a ferredoxin-like electron cartier for NiR (Fig. 5); NO~ assimilation consumes about 25% of the r e d u c t a n t generated from photosynthesis, shoot respiration, or root respiration (Figs.

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Arnold J. Bloom

1 a n d 7; B l o o m et al., 1989, 1992). C o n s e q u e n t l y , a p l a n t may e x p e n d m o r e t h a n o n e - q u a r t e r of its e n e r g y to a c q u i r e n i t r o g e n , a c o n s t i t u e n t t h a t usually c o m p r i s e s less t h a n 2% of total p l a n t dry weight. T h e p a r t i t i o n i n g of N O ] assimilation b e t w e e n r o o t a n d s h o o t varies a m o n g species (Andrews, 1986), b u t for m o s t species, s h o o t assimilation b e c o m e s increasingly i m p o r t a n t at h i g h e r light levels (Aslam a n d H u f f a k e r , 1982). U n d e r light-limited conditions, such as in a closed c a n o p y or u n d e r elevated a t m o s p h e r i c CO2 levels, N O ] or NO2 r e d u c t i o n is u n a b l e to comp e t e against c a r b o n fixation for p h o t o r e d u c t a n t a n d m u s t rely o n r e d u c t a n t g e n e r a t e d t h r o u g h r e s p i r a t i o n (Baysdorfer a n d Robinson, 1985; B l o o m et al., 1989). With i n c r e a s i n g light levels, as c a r b o n fixation b e c o m e s CO2 limited, N O ] or NO2 r e d u c t i o n may exploit the surplus r e d u c t a n t g e n e r a t e d f r o m p h o t o s y n t h e t i c e l e c t r o n t r a n s p o r t (Fig. 7; R o b i n s o n , 1986, 1988; B l o o m et al., 1989). Thus, d u r i n g N O ] a n d NO2 p h o t o a s s i m i l a t i o n , the h i g h

Figure 7 Influence of photosynthetic flux density (PFD) on n e t C O 2 influx (triangles) and net 02 effiux (circles) for the wild-type Steptoe barley (filled symbols) and a narla;naC7w mutant that is deficient in both NADH and NAD(P)H NO~ reductases (open symbols). The external CO2 concentration was 360/xl liter-1. The inset presents the dark CO2 and 02 fluxes on an expanded scale. Shown are the mean + SE (N = 3-8) with small error bars incorporated into the symbols. Net CO2 influx provides an estimate of carbon fixation in the light and carbohydrate catabolism in the dark; net O2 effiux provides an estimate of photosynthetic electron transport in the light and mitochondrial electron transport in the dark. Respiratory quotient (RQ) equals C O 2 e v o l v e d / O 2 . . . . . . . d" Assimilatory quotient (AQ) equals CO2 . . . . . . . d// Oz evolved.(A) Under NH~ nutrition, RQ and AQ did not deviate significantly from unity. (B) Under NO; nutrition, the wild type had a RQ and AQ that were significantly different from unity: CO2 fluxes were identical under NH~ and NOL but under NO~, 02 consumption in the dark was 25% less than CO2 evolution and 02 evolution at high light was 25% more than CO2 consumption. For the mutant, RQ in the dark and AQ at 1200/zmol m -2 sec-1 equaled unity. (Bloom et al., 1989).

5. Nitrogen as a Limiting Factor

157

e n e r g y d e m a n d s of these reactions do n o t divert c a r b o n assimilates f r o m growth or o t h e r processes.

D. Regulation of Nitrate Acquisition Both NO~ influx a n d N R activity increase several-fold u p o n first e x p o s u r e to NO~ (Bloom a n d S u k r a p a n n a , 1990; Siddiqi et al., 1990, 1992; Aslam et al., 1989, 1992); this i n d u c t i o n by the substrate NO~ provides for a coarse control of NO~ a b s o r p t i o n a n d assimilation. Fine control is effected t h r o u g h the following distinct mechanisms: 1. Root NO~ influx a n d efflux are, respectively, negatively a n d positively correlated with internal r o o t NO~ c o n c e n t r a t i o n (Fig. 8; Lee a n d Drew, 1986;Jackson, 1978; D e a n - D r u m m o n d a n d Glass, 1983; Teyker et al., 1988). As a c o n s e q u e n c e , efflux to the r h i z o s p h e r e is negligible until external c o n c e n t r a t i o n s reach high levels (Fig. 2), b u t a t 1500/zM (root NO~ contents of a b o u t 75 mol m -3 H 2 0 ) NO~ efflux may reach rates that e x c e e d 40% of influx (Lee a n d Clarkson, 1986). Most of the internal NO~ seems to be s e q u e s t e r e d in the vacuole (Lee a n d Clarkson, 1986). T h e r e f o r e , only newly a b s o r b e d NO~ or that released f r o m the vacuole influences N R activity (Aslam et al., 1976; MacKown et al., 1983).

Figure8 Net root uptake and root contents ofNH~ or NO~for tomato (Lycopersiconesculentum Mill. cv. T5) grown for several weeks in medium containing 20/zMNH4NO3 (open bars, light hatching) or 200/zM NH4NO3 (closed bars, heavy hatching). Nutrient concentrations were maintained to within 20% of the designated concentration and pH was controlled at pH 6.0 + 0.2. Steady-state root absorption of NH~or NO~was monitored from a solution containing 50 /zM NH4NOs. Root temperature was 20~ Shown are the mean _+ SE for six plants. The plants maintained relatively constant levels of NH~, whereas NOg contents increased significantly in the plants grown at 200/~M NH4NO~. These plants also absorbed NH~ or NO~ at a slower rate when exposed to an intermediate concentration. (Smart & Bloom, 1991).

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Arnold J. Bloom

2. Glutamine and several amino acids suppress both NOg absorption (Lee et al., 1992) and the amount of NR protein (Shiraishi, 1992). 3. Light stimulates NO~ absorption and NR activity. In plants that are carbohydrate limited, NOg absorption is greater during the day than at night (Clement et al., 1978; Aslam et al., 1979; Hansen, 1980; Pearson et al., 1981; Aslam and Huffaker, 1982; Rufty et al., 1984; Keltjens and Nijenstein, 1987). NR activity increases in the light both through changes in levels of the NR mRNA (Cheng et al., 1992) and through posttranslational phosphorylation of existing protein (Kaiser and Spill, 1991; Huber et al., 1992). A blue-light receptor and phytochrome may mediate the light responses of NO~ uptake in algae (Kamiya, 1989; Aparicio and Quifiones, 1991; L6pezFigueroa and R~diger, 1991; Corzo and Niell, 1992) and ofleafNR activity in higher plants (Duke and Duke, 1984; Schuster et al., 1989; Appenroth et al., 1992; Becker et al., 1992). All in all, internal root concentrations of NO; are not as finely regulated as those of NH] (Fig. 8; Smart and Bloom, 1991), probably because NO? can be stored in tissues without toxic effect (Goyal and Huffaker, 1984). Tissue NO~ provides plants with a storage pool to support growth when soil nitrogen availability becomes limiting (Chapin et al., 1990) and with a metabolically benign osmoticant during drought (Hanson and Hitz, 1983). A common scenario is for plants to accumulate relatively high levels of NO~ at the beginning of a growing season and then to some degree "coast" through the rest of the season (Chapin et al., 1990).

IV. Plant Growth as a Function of A m m o n i u m or Nitrate A. A m m o n i u m v e r s u s Nitrate

The relative reliance of crops on NH] and NO~ as nitrogen sources varies not only with soil availability but also with species. The capability of a species to use one form versus the other ranges from cranberry, which cannot use NO~ as a major nitrogen source (Greidanus et al., 1972), to radish, which cannot use NH] as the sole nitrogen source (Goyal et al., 1982). Most plants--even those that are native to flooded soils where NO~ levels in the bulk soil are negligible (Korcak, 1989; Koch et al., 1991)mperform better when they have access to both NH] and NO~ in the soil solution (cf Section II,A). Growth on a single nitrogen form not only produces shifts in rhizosphere pH but also changes the balance between inorganic cations and anions within plant tissues (Kirkby and Mengel, 1967; Arnozis and Findenegg, 1986; MacDuff et al., 1987); for example, growth on NH] as a sole nitrogen source may lead to deficiencies of cations, such as potassium or calcium, and accumulation to deleterious levels of anions such as borate

5. Nitrogen as a Limiting Factor

159

or molybdate (Fig. 9; Smart and Bloom, 1993). Cation-anion imbalances may be compensated by the production of organic acids (Raven and Smith, 1976), but the long-term effects of such compensation are unclear. Preference for one nitrogen form versus the other may change during plant development. Seedlings may be energy limited because light levels at the bottom of a canopy are usually low and the energy demands of seedling growth are great. Seedlings generally absorb more NH~ than NO? when both forms are available in equal amounts (A. Bloom, unpublished data) possibly because of the lower energy requirements for NH~ assimilation (approximately 2 ATP for NH~ vs 12 ATP for NO~; cf. Sections II,C and III,C). Similar factors may come into play near the end of the life cycle when canopies are closed: NH~ seems to stimulate crop reproduction (Marschner, 1995) and provide more nitrogen to seeds (Soares and Lewis, 1986) than does NO~.

B. Root Growth and Soil Nitrogen Availability Root systems must supply plants with water and nutrients u n d e r soil conditions that are extremely heterogeneous, both spatially and temporally (Jackson and Bloom, 1990). To optimize acquisition of a vital resource such as nitrogen, but minimize carbon expenditures for root structures,

Figure 9 Accumulation of boron and molybdenum in the tissue of tomato (Lycopersicon

Mill cv. T5) grown for 15-24 dayswith 20/zM NH~, 100/xMNH~, 20/zMNH~ and 50/xM NOL 50/zM NOL or 200/xM NO~ as the nitrogen source. Concentration is given in /zg of the element per gram dry weight root or shoot with the mean __ SE shown. (Smart and Bloom, 1993). esculentum

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Arnold J. Bloom

root production responds to local soil nitrogen levels (Hackett, 1972) in a hyperbolic fashion (Fig. 10; Bloom et al., 1993). In soil zones deficient in mineral nitrogen, root growth is minimal because it is nitrogen limited. As soil nitrogen availability increases, roots tend to proliferate (Drew, 1975; Grime et al., 1986; Granato and Raper, 1989; Jackson and Caldwell, 1989; Samuelson et al., 1991) and form denser architecture (Fitter et al., 1988; Fitter and Stickland, 1991). Where soil nitrogen exceeds an optimal l e v e l n i n our study on tomatoes, 2/zg N NH~ g-1 soil and 6/zg N NO~ g-1 soilmroot growth becomes carbohydrate limited, lags behind shoot growth, and eventually ceases (Boot and Mensink, 1990; Durieux et al., 1994; Marschner, 1995). With high soil nitrogen, a small proportion of the root system [3.5% in spring wheat (Robinson et al., 1991) and 12% in lettuce (Burns, 1991)] can supply all the nitrogen required by a plant so that a small root system may be sufficient. The optimization of root growth with soil nitrogen availability is consistent with the concept of a functional equilibrium between root and shoot (Brouwer, 1967; Brouwer and DeWit. 1969; Bloom et al., 1985). This concept proposes that because of the distances between sources and sinks, roots

Figure 10 Rootbiomass (/zg root dry weight g-1 soil) versus extractable soil NH] and NO~ (/zg extractable N g-~ soil) for Lycopersicon esculentum L. Mill. cv T5 growing in an irrigated field that had been fallow the previous 2 years. (Bloom et al., 1993).

5. Nitrogen as a Limiting Factor

161

m o r e readily m e e t their requirements for nitrogen than for carbohydrates, whereas shoots m o r e readily m e e t their requirements for carbohydrates than for nitrogen. U n d e r low soil nitrogen, the root and shoot growth is nitrogen limited a n d carbohydrate supply in the shoot is relatively high so that carbohydrate translocation to roots is high. W h e n a root encounters a soil patch rich in nitrogen, the nitrogen absorbed initially remains in that root and enhances growth. As the nitrogen levels in that root reach a surfeit, m o r e nitrogen is translocated to a shoot. Vascular connections often d e t e r m i n e that one part of the shoot receives a significant portion of its nutrients from a particular root and, in return, supplies carbohydrates first to that root (Watson and Casper, 1984; Wardlaw, 1990). This part of a shoot, now sufficient in nitrogen, becomes carbohydrate limited and translocates relatively little carbohydrate to the root; growth of this root then becomes carbohydrate limited. Such a response would explain the hyperbolic response of root production to soil nitrogen availability (Bloom et al., 1993; Durieux et al., 1994; Marschner, 1995).

C. Localization of Absorption and Its Immediate Effects Root tissue diminishes in activity as it matures (Marschner, 1995). As a result, nutrient absorption per unit root surface area is greatest in the i m m a t u r e tissues near the apex: In particular, root NH~ absorption reaches m a x i m u m rates within 1 m m of the apex (Figs. 11 and 12), whereas absorp-

Figure 11 Absorption of NH~ and NO] at various distances from the apex for nodal roots in rice. The measurements localize fluxes along the root axis to within 0.8 mm of the designated distance with 95% certainty. The diagram of the root approximates the morphology at various locations. (T. Colmer and A. Bloom, unpublished data).

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Figure 12 Absorption of NH~ and NOg at various distances from the apex of a maize seminal root. The measurements localize fluxes along the root axis to within 0.8 mm of the designated distance with 95 % certainty. The diagram of the root approximates the morphology at various locations. (T. Colmer and A. Bloom, unpublished data).

tion of NO~ (Figs. 11 and 12; Henriksen et al., 1992; Lazof et al., 1992) and of other ions such as K+ (Russell, 1977; Silk et al., 1986) reach a maximum in zones located 3-20 mm from the apex. Presumably, this rapid nutrient absorption serves the high demands of cell division and elongation that occur in these regions. Root hairs develop and xylem matures in regions more basal (Esau, 1960). Because the root hairs present a large surface area and the mature xylem provide better vascular connections, most of NO~ translocated to the shoot is absorbed in these more basal root zones (Lazof et al., 1992). Rapid NH~ or NO~ absorption in the zone of root elongation directly influences root growth and architecture. Root NH~ absorption stimulates proton effiux, whereas NO~ absorption involves cotransport with protons (cf Sections II,B and III,B; Allen, 1988); thus, these processes produce opposing pH shifts around the cell walls of elongating tissues. Protons released during NH~ absorption may displace Ca 2+ from the cell wall increasing its extensibility (Taiz and Zeiger, 1991) or stimulate wall loosening enzymes (Rayle and Cleland, 1992); in either case, root growth is stimulated in a p h e n o m e n o n known as the acid growth of roots (Tanimoto et al., 1989). Consequently, at physiological levels of rhizosphere nitrogen, root growth is more extensive under NH~ nutrition than under NO~ nutrition (Table I; Cox and Reisenauer, 1973; Rufty et al., 1983; Peet et al., 1985; Allen

5. Nitrogen as a Limiting Factor

163

and Smith, 1986; BlacquiSre et al., 1987; MacDuff et al., 1987; Anderson et al., 1991; Miller and Zhen, 1991; Bloom et al., 1993). Differences in the energy requirements of NH~ and NO~ acquisition may also influence growth under the two forms. In barley plants under NH~ nutrition, 14% of carbon catabolism was coupled to NH~ acquisition, whereas under NO~ nutrition, 5% of root carbon catabolism was coupled to NO~ absorption, 15% to NO] assimilation, and 3% to NH~ assimilation (Bloom et aL, 1992). Roots under NO] nutrition may be more carbohydrate limited and, thus, may grow more slowly (Bloom et al., 1993). The differential response of roots to rhizosphere NH~ and NO~ is reasonable in a ecological context. Ammonium binds strongly to cation-exchange sites on soil particles; the more extensive, finer roots that develop in the presence of NH~ are well suited to the task of increasing plant access to this bound NH~. Nitrate, by contrast, moves relatively freely through the soil; the thicker, perhaps less fragile, roots that develop in the presence of NO~ are probably adequate to access this mobile anion.

D. Research Opportunities Despite the importance of plant nitrogen acquisition to agricultural productivity, fundamental information about plant nitrogen relations is meager. Unknown are the mechanisms through which crops acquire nitrogen from the soil or the relative dependence of crops on various forms of soil nitrogen (i.e., ammonium, nitrate, or amino acids). There are only few data on how crop root systems develop in response to soil nitrogen availability or on what environmental signals roots use to be in the right place at the right time. Genetic variation in nitrogen harvest i n d e x ~ a measure of the ability to scavenge nitrogen from the soil and divert it into the harvested portions of the crop--remains virtually unexplored. Future efforts to manage our valuable nitrogen resources efficiently will require such information. Table I

The Plant Parameters (Mean _ SE, n = 4) of Shoot and Root Biomass (mgDw), Root Length (m), Root Branching (number m -1 root), and Root Area (cm a) for Lycopersicon esculentum Mill. cv. T5 Grown in Solution Culture for 12 Days under Constant Levels of Nitrogen Nutrition and pH a S h o o t biomass

Root biomass

Root l e n g t h

Root b r a n c h i n g

Root area

Treatment

(mgDw)

(mgDw)

(m)

(roots m -I)

(cm 2)

100/zMNH] 200 /.tM NO~

34.8 + 1.5 35.4 + 3.0

13.2 -+ 0.6 9.1 -+ 0.8

4.27 +- 0.19 3.00 _+ 0.23

34.9 _+ 1.6 28.1 -+ 0.8

17.3 -+ 0.8 12.9 -+ 1.5

a Shoot and root biomass data are from Smart and Bloom (1992); the other data are from Bloom et

al. (1992a).

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References Allen, S. (1988). Intracellular pH regulation in plants. ISI Atlas of Science. Anim. Plant Sci. 1,283-288. Allen, S., and Smith, J. A. C. (1986). Ammonium nutrition in Ricinus communis: Its effect on plant growth and the chemical composition of the whole plant, xylem and ploem saps. J. Exp. Bot. 37, 1599-1610. Amancio, S., and Santos, H. (1992). Nitrate and ammonium assimilation by roots of maize (Zea mays 1) seedlings as investigated by in vivo N-15 NMR. J. Exp. Bot. 43, 633-639. Anderson, D. S., Teyker, R. H., and Rayburn, A. L. (1991). Nitrogen form effects on early corn root morphological and anatomical development. J. Plant Nutr. 14, 1255-1266. Anderson, M. P., Vance, C. P., Heichel, G. H., and Miller, S. S. (1989). Purification and characterization of NADH-glutamate synthase form alfalfa root nodules. Plant Physiol. 90, 351-358. Andrews, M. (1986). The partioning of nitrate assimilation between roots and shoot of higher plants. Plant Cell Environ. 9, 511-519. Appenroth, K.-J., Oelmuller, R., Schuster, C., and Mohr, H. (1992). Regulation of transcript level and synthesis of nitrate reductase by phytochrome and nitrate in turions of Spirodela polyrhiz (L.) Schleiden. Planta 188, 587-593. Arnozis, P. A., and Findenegg, G. R. (1986). Electrical charge balance in the xylem sap of beet and sorghum plants grown with either NO~ or NH] nitrogen. J. Plant Physiol. 125, 441-449. Aslam, M., and Huffaker, R. C. (1982). In vivo nitrate reduction in roots and shoots of barley (Hordeum vulgare 1.) seedlings in light and darkness. Plant Physiol. 70, 1009-1013. Aslam, M., and Huffaker, R. C. (1989). Role of nitrate and nitrite in the induction of nitrite reductase in leaves of barley seedlings. Plant Physiol. 91, 1152-1156. Aslam, M., Oaks, A., and Huffaker, R. C. (1976). Effect of light and glucose on the induction of nitrate reductase and on the distribution of nitrate in etiolated barley leaves. Plant Physiol. 58, 588-591. Aslam, M., Huffaker, R. C., Rains, D. W., and Rao, K. P. (1979). Influence of light and ambient carbon dioxide concentration on nitrate assimilation by intact barley seedlings. Plant Physiol. 63, 1205-1209. Aslam, M., Travis, R. L., and Huffaker, R. C. (1992). Comparative kinetics and reciprocal inhibition of nitrate and nitrite uptake in roots of uninduced and induced barley (Hordeum vulgare L.) seedlings. Plant Physiol. 99, 1124-1133. Ayling, S. M. (1993). The effect of ammonium ions on membrane potential and anion flux in roots of barley and tomato. Plant Cell Environ. 16, 297-303. Baysdorfer, C., and Robinson, M.J. (1985). Metabolic interactions between spinach leaf nitrite reductase and ferredoxin-NADP reductase. Plant Physiol. 77, 318-320. Becker, T. W., Foyer, C., and Caboche, M. (1992). Light-regulated expression of the nitratereductase and nitrite-reductase genes in tomato and in the phytochrome-deficient aurea mutant of tomato. Planta 188, 39-47. Bertl, A., Felle, H., and Bentrup, F. W. (1984). Amine transport in Ricciafluitans: Cytoplasmic and vacuolar pH recorded by a pH-sensitive microelectrode. Plant Physiol. 76, 75-78. Blacqui~re, T., Hofstra, R., and Stulen, I. (1987). Ammonium and nitrate nutrition in Plantago lanceolata and Plantago major L. ssp. major. I. Aspects of growth, chemical composition and root respiration. Plant Soil 104, 129-141. Bloom, A.J. (1985). Wild and cultivated barleys show similar affinities for mineral nitrogen. Oecologia 65, 555-557. Bloom, A.J. (1988). Ammonium and nitrate as nitrogen sources for plant growth. ISI Atlas of Science. Anim. Plant Sci. 1, 55-59.

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Bloom, A. J. (1994). Crop acquisition of ammonium and nitrate. In "Physiology and Determination of Crop Yield" (K. J. Boote, J. M. Bennett, T. R. Sinclair, and G. M. Paulsen, eds.), pp. 303-309. ASA, CSA, SSSA, Madison, WI. Bloom, A. J., and Caldwell, R. M. (1988). Root excision decreases nutrient absorption and gas fluxes. Plant Physiol. 87, 794-796. Bloom, A.J., and Finazzo, J. (1986). The influence of ammonium and chloride on potassium and nitrate absorption by barley roots depends on time of exposure and cultivar. Plant Physiol. 81, 67-69. Bloom, A.J., and Sukrapanna, S. (1990). Effects of exposure to ammonium and transplant shock upon the induction of nitrate absorption. Plant Physiol. 94, 85-90. Bloom, A.J., Chapin, F. S., III, and Mooney, H. A. (1985). Resource limitation in plants--An economic analogy. Annu. Rev. Ecol. Syst. 16, 363-392. Bloom, A. J., Caldwell, R. M., Finazzo, J., Warner, R. L., and Weissbart, J. (1989). Oxygen and carbon dioxide fluxes from barley shoots depend on nitrate assimilation. Plant Physiol.

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Imsande, J., and Touraine, B. (1994). N demand and the regulation of nitrate uptake. Plant Physiol. 105, 3-7. Ingestad, T., and Agren, G. I. (1988). Nutrient uptake and allocation at steady-state nutrition. Physiol. Plant. 72, 450-459. Jackson, L. E., and Bloom, A.J. (1990). Root distribution in relation to soil nitrogen availability in field-grown tomatoes. Plant Soil 128, 115-126. Jackson, R. B., and Caldwell, M. M. (1989). The timing and degree of root proliferation in fertile-soil microsites for 3 cold-desert perennials. Oecolog~a 81, 149-153. Jackson, W. A. (1978). Nitrate acquisition and assimilation by higher plants: Processes in the root system. In "Nitrogen in the Environment" (D. R. Nielsen andJ. G. MacDonald, eds.), Vol. 2, pp. 45-88. Academic Press, New York. Kaiser, W. M., and Spill, D. (1991). Rapid modulation of spinach leaf nitrate reductase activity by photosynthesis. II. In vitro modulation by ATP and AMP. Plant Physiol. 96, 368-375. Kamiya, A. (1989). Effects of blue light and ammonia on nitrogen metabolism in a colorless mutant of Chlorella. Plant Cell Physiol. 30, 513-521. Keltjens, W. G., and Nijenstein, J. H. (1987). Diurnal variations in uptake, transport and assimilation of NO~ and effiux of OH- in maize plants. J. Plant Nutr. 10, 887-900. King, B. J., Siddiqi, M. Y., and Glass, A. D. M. (1992). Studies of the uptake of nitrate in barley. V. Estimation of root cytoplasmic nitrate concentration using nitrate reductase activity--Implications for nitrate influx. Plant Physiol. 99, 1582-1589. Kirkby, E. A., and Mengel, K. (1967). Ionic balance in different tissues of the tomato plant in relation to nitrate, urea, or ammonium nutrition. Plant Physiol. 42, 6-14. Kleiner, D. (1981). The transport of NH3 and NH] across biological membranes. Biochim. Biophys. Acta 639, 41-52. Kleiner, D. (1985). Bacterial ammonium transport. FEMS Microbiol. Rev. 32, 87-100. Knight, T. J., Durbin, R. D., and Langston-Unkefer, P.J. (1986). Effects of tabtoxinine-blactam on nitrogen metabolism in Avena sativa L. roots. Plant Physiol. 82, 1045-1050. Koch, G., and Bloom, A.J. (1989). Root respiration and NH] and NOg absorption in relation to root hypoxia in the wild variety of tomato, Lycopersicon esculentum var. cerasiforme. Plant Physiol. 89. [Abstract 717] Koch, G. W., Bloom, A.J., and Chapin, F. S., III (1991). Ammonium and nitrate as nitrogen sources in two Eriophorum species. Oecologia 88, 570-573. Korcak, R. F. (1989). Variation in nutrient requirements of blueberries and other calcifuges. Hort. Sci. 24, 573-578. Kosola, K. R., and Bloom, A.J. (1994). Methylammonium as a transport analog for ammonium in tomato (Lyc0persic0n esculentum Mill.). Plant Physiol. 104, 435-442. Kosola, I~ R., and Bloom, A.J. (1996). Chlorate as a transport analog for nitrate absorption by roots of tomato (Lycopersicon esculentum). Plant Physiol., 110, 1293-1299. Kronzucker, H.J., Siddiqi, M. Y., and Glass, A. D. M. (1995). Analysis of (NH])-N 13 effiux in spruce roots--A test case for phase identification in compartmental analysis. Plant Physiol. 109, 481-490. Kurkdjian, A., and Guern, J. (1989). Intracellular pH: Measurement and importance in cell activity. Annu. Rev. Plant Physiol. 40, 271-303. Lam, H. M., Coschigano, K. T., Oliveira, I. C., Melooliveira, R., and Coruzzi, G. M. (1996). The molecular-genetics of nitrogen assimilation into amino acids in higher plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 47, 569-593. Lazof, D. B., Rufty, T. W., Jr., and Redinbaugh, M. G. (1992). Localization of nitrate absorption and translocation within morphological regions of the corn root. Plant Physiol. 100, 12511258. Lee, R. B., and Clarkson, D. T. (1986). Nitrogen-13 studies on nitrate fluxes in barley roots. I. Compartmental analysis from measurements of 13N effiux. J. Exp. Bot. 37, 1753-1767.

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Lee, R. B., and Drew, M. C. (1986). Nitrogen-13 studies of nitrate fluxes in barley roots. II. Effect of plant N-status on the kinetic parameters of nitrate influx.J. Exp. Bot. 37,1768-1779. Lee, R. B., and Ratcliffe, R. G. (1991). Observations on the subcellular distribution of the ammonium ion in maize root tissue using in vivo N14nuclear-magnetic-resonance spectroscopy. Planta 183, 359-367. Lee, R. B., and Rudge, K. A. (1986). Effects of nitrogen deficiency on the absorption of nitrate and ammonium by barley plants. Ann. Bot. 57, 471-486. Lee, R. B., Purves, J. v., Ratcliffe, R. G., and Saker, L. R. (1992). Nitrogen assimilation and the control of ammonium and nitrate absorption by maize roots.J. Exp. Bot. 43, 1385-1396. Lewis, O. A. M. (1986). "Plants and Nitrogen," pp. 104. Arnold, London. Loomis, R. S., and Conner, D.J. (1992). "Crop Ecology: Productivity and Management in Agricultural Systems." Cambridge Univ. Press, Cambridge, UK. Ltpez-Figueroa, F., and ROdiger, W. (1991). Stimulation of nitrate net uptake and reduction by red and blue light and reversion by far-red light in the green alga Ulva rigida. J. Phycol. 27, 389-394. Lorenz, O. A. (1978). Potential nitrate levels in edible plant parts. In "Nitrogen in the Environment" (D. R. Nielsen and J. G. MacDonald, eds.), Vol. 2, pp. 201-219. Academic Press, San Diego. Lycklama, J. C. (1963). The absorption of ammonium and nitrate by perennial rye-grass. Acta Bot. Need. 12, 361-423. Lynch, J. (1995). Root architecture and plant productivity. Plant Physiol. 109, 7-13. MacDuff, J. H., Hopper, M.J., and Wild, A. (1987). The effect of root temperature on growth and uptake of ammonium and nitrate by Brassica napus L. in flowing solution culture. I. Growth. J. Exp. Bot. 38, 42-52. MacKown, C. T., Jackson, W. A., and Volk, R.J. (1983). Partitioning of previously-accumulated nitrate to translocation, reduction, and effiux in corn roots. Planta 157, 8-14. Marcus-Wyner, L. (1983). Influence of ambient acidity on the absorption of NOg and NH~ by tomato plants. J. Plant Nutr. 6,657-666. Marschner, H. (1995).' 'Mineral Nutrition of Higher Plants, 2nd Ed." Academic Press, London. McClure, P. R., Kochian, L. V., Spanswick, R. M., and Shaft, J. E. (1990). Evidence for cotransport of nitrate and protons in maize roots. I. Effects of nitrate on the membrane potential. Plant Physiol. 93, 281-289. Meyerhoff, P. A., Fox, T. C., Travis, R. L., and Huffaker, R. C. (1994). Characterization of the association of nitrate reductase with barley (Hordeum vulgare L.) root membranes. Plant Physiol. 104, 925-936. Miller, A.J., and Zhen, R. G. (1991). Measurement of intracellular nitrate concentrations in Chara using nitrate-selective microelectrodes. Planta 184, 47-52. Minotti, P. L., Williams, D. C., and Jackson, W. A. (1968). Nitrate uptake and reduction as affected by calcium and potassium. Soil Sci. Soc. Am. Proc. 32, 692-698. Morgan, M. A., and Jackson, W. A. (1988a). Inward and outward movement of ammonium in root systems: Transient responses during recovery from nitrogen deprivation in presence of ammonium. J. Exp. Bot. 39, 179-191. Morgan, M. A., and Jackson, W. A. (1988b). Suppression of ammonium uptake by nitrogen supply and its relief during nitrogen limitation. Physiol. Plant. 73, 38-45. Morgan, M. A., and Jackson, W. A. (1989). Reciprocal ammonium transport into and out of plant roots: Modifications by plant nitrogen status and elevated root ammonium concentration. J. Exp. Bot. 40, 207-214. Munn, D. A., and Jackson, W. A. (1978). Nitrate and ammonium uptake by rooted cuttings of sweet potato. Agron. J. 70, 312-316. National Research Council (1989). "Alternative Agriculture." National Academy Press, Washington, DC.

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Nicoulaud, B. A. L., and Bloom, A.J. (1994). Foliar applied urea as the sole nitrogen source on tomato plants to study ammonium acquisition by the roots. Plant Physiol. 105. [Abstract 136] Novoa, R., and Loomis, R. S. (1981). Nitrogen and plant production. Plant Soil 58, 177-204. Nye, P. H., and Tinker, P. B. (1977). "Solute Movement in the Soil-Root System." Univ. of California Press, Berkeley. Nylund, J. E. (1990). Nitrogen, carbohydrate and ectomycorrhiza--The classical theories crumble. Agric. Ecol. Environ. 28, 361-364. Oaks, A. (1994). Efficiency of nitrogen utilization in C~ and C4 cereals. Plant Physiol. 106, 1-7. Oaks, A., and Hirel, B. (1985). Nitrogen metabolism in roots. Annu. Rev. Plant Physiol. 36, 345-365. Oaks, A., and Long, D. M. (1992). NO] assimilation in root systems: With special reference to Zea mays (cv. W64A X W128E). In "Nitrogen Metabolism of Plants" (K. Mengel and D.J. Pilbeam, eds.), Proc. Phytochem. Soc. Europe, Vol. 3, pp. 91-102. Clarendon, Oxford. Pearson, C. J., Volk, R.J., and Jackson, W. A. (1981). Daily changes in nitrate influx, effiux and metabolism in maize and pearl millet. Planta 152, 319-324. Peet, M. M., Raper, D. C., Tolley, L. C., and Robarge, W. P. (1985). Tomato responses to ammonium and nitrate nutrition under controlled root-zone pH. J. Plant Nutr. 8, 787-798. Peoples, M. B., and Craswell, E. T. (1992). Biological nitrogen fixation: Investments, expectations and actual contributions to agriculture. Plant Soil 141, 13-39. Pitts, R. F. (1972). Control of renal production of ammonia. Kidney Int. 1,297-305. Raven, J. A., and Smith, F. A. (1976). Nitrogen assimilation and transport in vascular land plants in relation to intracellular pH regulation. New Phytol. 76, 415-431. Rayle, D. L., and Cleland, R. E. (1992). The acid growth theory of auxin-induced cell elongation is alive and well. Plant Physiol. 99, 1271-1274. Reisenauer, H. M. (1978). Absorption and utilization of ammonium nitrogen by plants. In "Nitrogen in the Environment" (D. R. Nielsen andJ. MacDonald, eds.), Vol. 2, pp. 157-170. Academic Press, New York. Roberts, J. K. M., and Pang, M. K. L. (1992). Estimation of ammonium ion distribution between cytoplasm and vacuole using nuclear magnetic resonance spectroscopy. Plant Physiol. 100, 1571-1574. Robinson, D. (1986). Compensatory changes in the partitioning of dry matter in relation to nitrogen uptake and optimal variations in growth. Ann. Bot. 58, 841-848. Robinson, D., Linehan, D.J., and Caul, S. (1991). What limits nitrate uptake from soil? Plant Cell Environ. 14, 77-85. Robinson, J. M. (1986). Carbon dioxide and nitrite photoassimilatory processes do not intercompete for reducing equivalents in spinach and soybean leaf chloroplasts. Plant Physiol. 80, 676-684. Robinson, J. M. (1988). Spinach leaf chloroplast CO2 and NO2 photoassimilations do not compete for photogenerated reductant. Manipulation of reductant levels by quantum flux density titrations. Plant Physiol. 88, 1373-1380. Rufty, T. W., Jr., Jackson, W. A., and Raper, C. D.,Jr. (1982). Inhibition of nitrate assimilation in roots in the presence of ammonium. The moderating influence of potassium. J. Exp. Bot. 33, 1122-1137. Rufty, T. W., Jr., Raper, C. D.,Jr., and Jackson, W. A. (1983). Growth and nitrogen assimilation of soybeans in response to ammonium and nitrate nutrition. Bot. Gaz. 144, 466-470. Rufty, T. W., Raper, C. D., Jr., and Huber, S. C. (1984). Alterations in internal partitioning of carbon in soybean plants in response to nitrogen stress. Can. J. Bot. 62, 501-508. Russell, R. S. (1977). "Plant Root Systems. Their Function and Interaction with the Soil." McGraw-Hill, London. Samuelson, M. E., Eliasson, L., and Larsson, C.-M. (1991). Nitrate-regulated growth and cytokinin responses in seminal roots of barley. Plant Physiol. 98, 309-315.

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Sasakawa, H., and Yamamoto, Y. (1978). Comparison of the uptake of nitrate and ammonium by rice seedlings. Influences of light, temperature, oxygen concentration, exogenous sucrose, and metabolic inhibitors. Plant Physiol. 62, 665-669. Scherer, H. W., MacKnown, C. T., and Leggett, J. E. (1984). Potassium-ammonium uptake interactions in tobacco seedlings. J. Exp. Bot. 35, 1060-1070. Schortemeyer, M., Feil, B., and Stamp, P. (1993). Root morphology and nitrogen uptake of maize simultaneously supplied with ammonium and nitrate in a split-root system. Ann. Bot. 72, 107-115. Schuster, C., Schmidt, S., and Mohr, H. (1989). Effect of nitrate, ammonium, light and a plastidic factor on the appearance of multiple forms of nitrate reductase in mustard (Sinapis alba L. ) cotyledons. Planta 177, 74-83. Schwerdffeger, W. (1976). "World Survey of Climatology. Vol. 12." Elsevier, New York. Serrano, R. (1989). Structure and function of plasma membrane ATPase. Annu. Rev. Plant Physiol. 40, 61-94. Shiraishi, N., Sato, T., Ogura, N., and Nakagawa, H. (1992). Control by glutamine of the synthesis of nitrate reductase in cultured spinach cells. Plant Cell Physiol. 33, 727-731. Siddiqi, M. Y., Glass, A. D. M., Ruth, T.J., and Rufty, T. W. (1990). Studies of the uptake of nitrate in barley. 1. Kinetics of l~NO~-influx. Plant Physiol. 93, 1426-1432. Siddiqi, M. Y., King, B.J., and Glass, A. D. M. (1992). Effects of nitrite, chlorate, and chlorite on nitrate uptake and nitrate reductase activity. Plant Physiol. 100, 644-650. Silk, W. H., Hsiao, T. C., Diedenhofen, U., and Matson, C. (1986). Spatial distribution of potassium, solutes and their deposition rates in the growth zone of the primary corn root. Plant Physiol. 82, 853-858. Smart, D. R., and Bloom, A.J. (1988). Kinetics of ammonium and nitrate uptake among wild and cultivated tomatoes. Oecologia 76, 336-340. Smart, D. R., and Bloom, A.J. (1991). Influence of root NH~ and NO~ content on the temperature response of net NH~ and NO~ uptake in chilling sensitive and chilling resistant Lycopersicon taxa. J. Exp. Bot. 42, 331-338. Smart, D. R., and Bloom, A.J. (1993). The relationship between kinetics of NH~ and NO~ absorption and growth in the cultivated tomato (Lyc0persic0n esculentum Mill. cv. T5). Plant Cell Environ. 16, 259-267. Smith, F. A., and Walker, N. A. (1978). Entry of methylammonium and ammonium ions into Chara internodal cells. J. Exp. Bot. 29, 107-120. Soares, M. I. M., and Lewis, O. A. M. (1986). An investigation into nitrogen assimilation and distribution in fruiting plant of barley (Hordeum vulgare L. cv. Clipper) in response to nitrate, ammonium and mixed nitrate and ammonium nutrition. New Phytol. 104, 385-393. Suzuki, A., and Gadal, P. (1984). Glutamate synthase: Physiochemical and functional properties of different forms in higher plants and other organisms. Physiol. Veg. 22, 471-486. Suzuki, A., Gadal, P., and Oaks, A. (1981). Intracellular distribution of enzymes associated with nitrogen assimilation in roots. Planta 151,457-461. Suzuki, A., Vidal,J., and Gadal, P. (1982). Glutamate synthase isoforms in rice. Immounological studies of enzymes in green leaf, etiolated leaf, and root tissues. Plant Physiol. 78, 374-378. Syrett, P.J., and Peplinska, A. M. (1988). Effects of nitrogen-deprivation, and recovery from it, on the metabolism of microalgae. New Phytol. 109, 289-296. Taiz, L., and Zeiger, E. (1991). "Plant Physiology." Benjamin/Cummings, Redwood City, CA. Talouizte, A., Champigny, M. L., Bismuth, E., and Moyse, A. (1984). Root carbohydrate metabolism associated with nitrate assimilation in wheat previously deprived of nitrogen. Physiol. Veg. 22, 19-27. Tanimoto, E., Scott, T. K., and Masuda, Y. (1989). Inhibition of acid-enhanced elongation of Zea mays root segments by galactose. Plant Physiol. 90, 440-444. Tennessee Valley Authority (1991). "Commercial Fertilizers 1991." National Fertilizer and Environmental Research Center, Muscle Shoals, AL.

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Teyker, R. H., Jackson, W. A., Volk, R.J., and Moll, R. H. (1988). Exogenous I~NO] influx and endogenous 14NO] effiux by two maize (Zea mays L.) inbreds during nitrogen deprivation. Plant Physiol. 86, 778-781. Thibaud, J. B., and Grignon, C. (1981). Mechanism of nitrate uptake in corn roots. Plant Sci. Lett. 22, 279-289. Tingey, S. V., Walker, E. L., and Coruzzi, G. M. (1987). Glutamine synthetase genes of pea encode distinct polypeptides which are differentially expressed in leaves, roots and nodules. EMBOJ. 6, 1-9. Tolley-Henry, L., and Raper, C. D.,Jr. (1986). Utilization of ammonium as a nitrogen source. Effects of ambient acidity on growth and nitrogen accumulation by soybean. Plant Physiol. 82, 54-60. Tyerman S. D. (1992). Anion channels in plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 43, 351-373. Tyerman, S. D., Findlay, G. e., and Paterson, G.J. (1986). Inward membrane current in Chara inflata. II. Effects of pH, C1- channel blockers and NH~, and significance of the hyperpolarised state. J. Membrane Biol. 89, 153-161. Ullrich, W. R. (1987). Nitrate and ammonium uptake in green algae and higher plants: Mechanism and relationship with nitrate metabolism. In "Inorganic Nitrogen Metabolism" (W. R. Ullrich, e. J. Aparicio, e.J. Syrett, F. Castillo, eds.), pp. 32-38. Springer-Verlag, New York. Ullrich, W. R. (1992). Transport of nitrate and ammonium through plant membranes. In "Nitrogen Metabolism of Plants" (K. Mengel and D.J. Pilbeam, eds.), Proc. Phytochem. Soc. Europe, Vol. 3, pp. 121-137. Clarendon, Oxford. Ullrich, W. R., and Novacky, A. (1981). Nitrate-dependent membrane potential changes and their induction in Lemna gibba G1. Plant Sci. Lett. 22, 211-217. Ullrich, W. R., Larsson, M., Larsson, C.-M., Lesch, S., and Novacky, A. (1984). Ammonium uptake in Lemna gibba G 1, related membrane potential changes, and inhibition of anion uptake. Physiol. Plant. 61,369-376. Vale, F. R., Volk, R.J., and Jackson, w. A. (1988). Simultaneous influx of ammonium and potassium into maize roots: Kinetics and interactions. Planta 173, 424-431. van Keulen, H., and van Heemst, H. D.J. (1982). Crop response to the supply of macronutrients. Agric. Res. Rep. No. 916. Centre for Agricultural Publishing and Documentation, Wageningen. Vaughn, K. C., and Campbell, W. H. (1988). Immunogold localization of nitrate reductase in maize leaves. Plant Physiol. 88, 1354-1357. Vessey, J. K., Henry, L. T., Chaillou, S., and Raper, C. D. (1990). Root-zone acidity affects relative uptake of nitrate and ammonium from mixed nitrogen sources. J. Plant Nutr. 13, 95-116. Vezina, L.-P., and Langlois,J. R. (1989). Tissue and cellular distribution of glutamine synthetase in roots of pea (Pisum sativum) seedlings. Plant Physiol. 90, 1129-1133. Walker, D.J., Smith, S.J., and Miller, A.J. (1995). Simultaneous measurement of intracellular pH and K+ or NO~ in barley root cells using triple-barreled, ion-selective microelectrodes. Plant Physiol. 108, 743-751. Wang, M. Y., Siddiqi, M. Y., Ruth, T. J., and Glass, A. D. M. (1993). Ammonium uptake by rice roots I. Fluxes and subcellular distribution of 13NH~. Plant Physiol. 103, 1249-1258. Ward, M. R., Grimes, H. D., and Huffaker, R. C. (1989). Latent nitrate reductase activity is associated with the plasma membrane of corn roots. Planta 177, 470-475. Wardlaw, I. F. (1990). The control of carbon partitioning in plants. New Phytol. 116, 341-381. Watson, M. A., and Casper, B. B. (1984). Constraints on the expression of plant phenotypic plasticity. Annu. Rev. Ecol. Syst. 15, 233-258. Zhen, R. G., Koyro, H. W., Leigh, R. A., Tomos, A. D., and Miller, A.J. (1991). Compartmental nitrate concentrations in barley root cells measured with nitrate-selective microelectrodes and by single-cell sap sampling. Planta 185, 356-361.

6 Trade-offs in Root Form and Function

David M. Eissenstat

I. Introduction Agricultural research on roots has focused primarily on attributes of root systems and their mycorrhizal fungi that might be enhanced for acquisition of water and nutrients or tolerance to salinity, heavy metals, low soil water potentials, or specific root pathogens. Much less attention has been focused on the potential trade-offs between different modes of root deployment. For example, a large extensive root system of high root length density is desirable from a water or nutrient acquisition perspective but may come at a carbon cost not consistent with optimizing yield. Similarly, roots constructed to be well defended against herbivores and pathogens may be slow growing and have heavily suberized and lignified epidermal and cortical cell walls (Ryser, 1996); these traits are not consistent with roots designed to maximize water and nutrient uptake. The concepts of ecological tradeoffs may aid in understanding root form and function as well as enhance opportunities for improved breeding and m a n a g e m e n t of crops. In this chapter, I will review root deployment from a cost: benefit perspective, placing particular emphasis on work in citrus. I will cover how design of the optimal root system for such parameters as r o o t : s h o o t ratio, root diameter, root maintenance respiration, root architecture, root hydraulic conductivity, root defense, root life span, and root symbiosis with mycorrhizal fungi must be considered in the context of relative resource availabilities. Cultivars adapted to drought, infertile soils, or defense from root-feeding Ecology in Agriculture

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organisms will likely have different root systems from those most suitable to highly intensive agriculture.

II. Citrus as a Model System Annual crops are of great agricultural importance and their root systems, especially in cereals, have been studied extensively. Perennial dicots also have high agricultural importance but have received much less research attention. In reviewing trade-offs in roots systems, it is important to consider the unique ecological niche of annuals. For example, annual plants typically grow very fast from seed and finish their life cycle during the growing season. They are found most frequently in disturbed habitats a n d / o r habitats with a long dry season. Perennial species, in contrast, often build root systems that can support a shoot many meters tall; survive periods of the year when minimal C is imported from the shoot; support shoot regrowth following canopy loss; tolerate wide fluctuations in soil temperature, soil water potential, oxygen availability, and h e r b i v o r e / p a t h o g e n pressure; and provide the internal meristems necessary for the continuous production of new fine laterals needed to replace those that have died. Thus, although ecological trade-offs occur in annuals, many kinds of trade-offs in root form and function are most vividly expressed in perennial root systems. Citrus is an example of a crop that exhibts many kinds of trade-offs in its root systems. Citrus is a subtropical evergreen that is believed to be an understory tree in the parts of Asia where it originated. In fruit crops like citrus, rootstocks can be specifically targeted for certain environmental conditions, such as tolerance to flooding, saline soil, or root feeding by nematodes or fungal pathogens. Trees may be grown without irrigation for sometimes greater than 30 years. Therefore, citrus growers must choose from a diverse group of rootstocks based on site conditions, scion variety, desired tree size, and other m a n a g e m e n t objectives. These rootstocks have not been selected based on fruit characteristics. Indeed, many rootstocks produce an inedible fruit. Besides being adapted to a wide set of environmental conditions, an additional advantage of using rootstocks is that inferences about the role of the root system are strengthened because the roots of species of Citrus and related genera are compared on a c o m m o n site with all the scions (shoots) genetically identical, thus providing an important internal control. Citrus rootstocks vary widely in root morphology, n u m b e r and depth of structural roots, hydraulic conductivity, mycorrhizal dependency, and plant growth rates (Castle, 1987; Eissenstat, 1991, 1992; Graham and Eissenstat, 1994). Thus, they provide an excellent system to examine potential trade-offs in the structure and function of root systems.

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III. Optimizing Carbon Expenditure on Roots Physiological ecologists commonly have taken a cost: benefit or economic approach to understanding how plants cope with the availability of light, water, and nutrients (Bloom et al., 1985; Chapin et al., 1987). The view that plants are typically limited by several resources simultaneously is an important departure from the more traditional view of single resource limitation developed by the German chemist, Justus von Liebig, in the 19th century and that dominated the thinking of agricultural workers for a very long time (Tisdale and Nelson, 1975). Carbon has been widely used by physiological ecologists as a currency for estimating costs of allocation, tissue construction, and resource acquisition because C provides an indirect measure of energy gain and expenditure by the plant and because the rate of energy capture often limits plant growth (Chapin, 1989). Carbon limitation is most clearly demonstrated by the numerous incidences of enhanced whole plant growth when plants are exposed to elevated CO2 (Rogers et al., 1994). Other resources, however, such as N or P, can also be a useful currency in understanding costs and benefits, especially in strongly nutrient-limited environments in which C supply does not limit plant growth (Chapin, 1989; Eissenstat and Yanai, 1997). A. The Balance between Shoot and Root Growth

An obvious example illustrating the evidence that carbon expenditure below ground can significantly affect shoot growth is the close coordination between shoot and root partitioning with nutrient supply (e.g., Ingestad and Agren, 1991). When plants have constant relative growth rates and constant internal nutrient concentrations, the fraction ofbiomass allocated to the shoot is positively correlated with plant nutrient status (for N, P, and S but not K). Plants have higher relative growth rates when they are of higher nutrient status (until saturation). Taking a simple crop modeling approach, the primary role of the shoots is to fix C for the plant, which is proportional to shoot activity (photosynthesis) and total leaf mass (or area) (e.g., Thornley and Johnson, 1990). The primary role of the roots is to acquire water and nutrients, which are a product of root activity and root mass (area). Leaf growth and photosynthesis is dependent on water and nutrients from the roots; root growth and activity is dependent on C from the shoots. This "functional equilibrium" between roots and shoots is a basic tenet of most crop growth models. For example, in sour orange seedlings grown at a range of P supply, relative growth rate was inversely related to root:shoot ratio (Eissenstat et al., 1993). This principlemthat when soil resources are limiting, plants must allocate a greater proportion of photosynthate to the roots, thus causing slower whole plant relative growth ratesmrepresents a widely recognized trade-

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off of root production. Other aspects associated with trade-offs in root construction, such as root respiration, root morphology, and root architecture, however, are often ignored. B. R o o t C o n s t r u c t i o n v e r s u s M a i n t e n a n c e

Roots represent a considerable C cost (e.g., Caldwell, 1979). In perennial communities of natural ecosystems (e.g., grasslands, tundra, and evergreen forests), annual biomass production below ground usually exceeds that above ground (Caldwell, 1987; Fogel, 1985). In addition to C allocated for root production, C allocated for root respiration is also high (Table I). Root respiration can be partitioned into respiration used for root growth, root maintenance, and ion uptake and assimilation. Respiration used for the uptake and assimilation of nutrients is a cost associated more with whole plant function and will not be considered further. Maintenance respiration of the fine roots of a wide range of species is approximately 2 mmol C g-a day-1 (range, 1-4 mmol C g - 1 day-a; see Amthor, 1984; Peng et al., 1993). The total cost (growth respiration and root C content) to build roots, typically referred to as the construction cost, can range from 42 to 49 mmol C g-m dry weight (dw) (Peng et al., 1993; Amthor et al., 1994). Thus, in just 20-26 days the C expended on root maintenance can

Table I

Summary of Root Respiratory Costs of Volkamer Lemon Seedlings Colonized by Glomus intraradices (M) or Uninoculated (NM) a 1P M

5P NM

M

NM

Cost per unit root dry wt [mmol C02 (g new root)- i] C o n s t r u c t i o n cost Growth respiration coefficient

48.7 11.8

44.7 10.1

45.3 10.3

42.0 8.7

Specific respiration rates [mmol C02 (g whole root system)- i days-l] Total root respiration Ion-uptake respiration M a i n t e n a n c e respiration b No. of days for m a i n t e n a n c e respiration to equal cost of root construction

4.14 0.83 2.46 19.8

3.00 0.72 1.77 25.3

3.00 0.40 2.05 22.1

2.61 0.48 1.62 25.9

a From Peng et al. (1993) and Eissenstat and Yanai (1997). Plants were grown at either low- or high-P supply (1P = 1 mM K H 2 P 0 4 ; 5 P = 5 mM P added once or twice per week, depending on plant size). bMaintenance respiration represents respiration not attributable to growth or ion uptake and, thus, includes maintenance of roots and fungal biomass in the root, microbial respiration of plant exudates, and respiration of extramatrical hyphae.

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exceed the C e x p e n d e d on root construction (Table I). Clearly, the C e x p e n d e d on root growth and maintenance is a considerable cost to the plant. If only a small a m o u n t of C was diverted from growth and maintenance of roots to new shoot growth then the C investment could be compounded, leading to an exponential increase in growth (under conditions in which plant growth is partially limited by C).

IV. Parallels between Roots and Leaves When analyzing the potential trade-offs in root deployment, it is useful to draw upon the rich ecological literature on leaves. Fine roots and leaves are both generally ephemeral tissues, with a single dominant function: resource acquisition. Leaves have one primary function: acquisition of C. Roots are usually separated into fine roots and coarse roots (often based on some arbitrarily chosen root diameter, e.g., 2 mm). Coarse roots are primarily designed for extending the root system vertically and laterally, transporting water and nutrients from the fine roots to the stem, anchoring the stem in the soil, and storing carbohydrates and mineral nutrients. Although fine roots may serve minor functions in storage, anchorage, and transport, the primary function of fine roots is water and nutrient acquisition. In leaves, many traits are associated with long life span including low resource availability in the plant's preferred habitat, low m a x i m u m plant growth rates, low m a x i m u m photosynthetic rates, low dark respiration rates, low specific leaf area (area/dry wt), and high tissue density (Table II). Similar relationships may also be true in roots (Eissenstat, 1992). Long-

Table II

Characteristics Hypothesized to Be Associated with Leaf and Root Life Span a Variable

Max. potential growth rate Responses to pulses or patches of nutrients Max. rates of photosynthesis or nutrient and water absorption Maintenance respiration rates Specific leaf area or root length Tissue density Amount of tissue construction allocated to antiherbivore defense Successional status Resource availability in native habitat

Short life span

Long life span

High High High

Low Low Low

High High Low Low

Low Low High High

Often early High

Often late Low

aFrom Coley et al. (1985), Coley (1988), Eissenstat (1992), Reich et al. (1992), Chapin (1993), Garnier and Laurent (1994), Grime (1994), Ryser (1996), and Eissenstat and Yanai (1996).

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lived roots may tend to be coarse, invest more in immobile defenses, have low hydraulic conductivity, low specific ion absorption rates, low maintenance respiration rates, and less flexible responses to pulses in resources (Table II). Screening crop cultivars for high root growth rates or rates of ion uptake in young seedlings may represent trade-offs in root longevity and tolerance to edaphic stresses. Ecological theory suggests that resource availability (e.g., light, water, and nutrients) places a large constraint on the relative advantages of different kinds of tissue deployment. In some agricultural sectors production is moving toward lower inputs of irrigation, pesticides, and fertilizers in the hopes of higher efficiency and lower agrochemical pollution. More than 80% of the world's population is located in countries whose soils are of relatively low fertility and whose agriculturists can not afford costly agrochemical inputs (World Bank, 1993). In designing crop plants that can meet these environmental conditions, roots that are coarser, slower growing but better defended, with lower maintenance costs, may represent an important breeding objective, especially for perennial crops.

V. Specific Root Length, Root Diameter, and Tissue Density Specific root length (SRL) is defined as the length:dry mass ratio of the fibrous root system. It has been used as a rough measure of the benefit (length) versus cost (drywt) of the root system (e.g., Fitter, 1991). Mechanistic modeling of nutrient uptake would suggest that the most efficient deployment of root mass is to build very fine roots that maximize length and absorptive surface area per gram dry weight of root (Barber and Silberbush, 1984; Yanai et al., 1995). Presumably, there are important trade-offs in building very fine roots not being considered in these nutrient uptake models (Eissenstat, 1992). Plant species vary widely in root diameter. The diameter of the finest elements of the root system can be less than 100/zm in many graminoid species found in theJuncaceae, Cyperaceae, and Poaceae, in ericoid mycorrhizal species of the Ericaceae and Epacridaceae, and in many annual dicots such as the well-studied species, Arabidopsis thaliana (Harley and Smith, 1983; Fitter, 1991; Eissenstat, 1992, unpublished data). At the other extreme, many woody species found in the Magnoliaceae, Pinaceae, and Rutaceae (family of Citrus) and herbaceous species found in the Alliaceae produce absorptive roots that are no finer than 500-1000/zm in diameter. It is normally assumed that SRL is proportional to the square of the root radius. This, of course, assumes the density of the tissue is largely constant. In citrus rootstock genotypes, a range of root diameters of 5 8 7 - 6 8 8 / z m

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corresponded to a 44% difference in root l e n g t h / r o o t volume (Table III). Among these same genotypes, however, there was an 83% difference in SRL; the genotypes that built the finest roots also built roots with the lowest tissue density (Eissenstat, 1991). The rootstocks with the smallest diameter roots and lowest tissue density were able to proliferate roots in disturbed soil faster than the rootstock genotypes with coarse roots and higher tissue density (Fig. 1, top). Citrus rootstocks that produced greater root length in the disturbed soil also depleted water to a greater extend 8 days following a saturating rain (Fig. 1, bottom). Fitter (1994) found a similar relationship of root diameter with root proliferation when investigating root growth in nutrient patches among four herbaceous species in the Caryophyllaceae. He found a strong inverse relationship between mean root diameter and the ratio of relative extension rate (RER) in the patch to RER in the nutrient poor patch. Ryser and Lambers (1995) identified tissue density as having a fundamental role in distinguishing traits of ecologically distinct grasses. They found that the slow-growing grass, Brachypodium pinnatum, had 20-106% higher root tissue density than the fast-growing grass, Dactylis glomerata. They suggest that production of roots at low tissue density, especially at low to moderate N supply, allows D. glomeratato explore much greater soil volumes than the slower-growing B. pinnatum. Similar relationships of high RGR with low tissue density have been found in leaves; both of these traits have been linked to shorter tissue longevity (Poorter and Remkes, 1990; Garnier and Laurent, 1994; Ryser, 1996). Thus, there is some evidence among the roots of the fine root system that dense, highly lignified and tannified Table III

Patterns of Root Biomass Allocation among Six Citrus Rootstocks a Fibrous roots P i o n e e r roots

Rootstock

Root diameter b (/zm)

Sour o r a n g e Cleopatra mandarin Swingle c i t r u m e l o Rough lemon Volkamer lemon Trifoliate o r a n g e LSD (0.05)

665 688 673 637 632 587 44

Length/vol. (cm -2)

SRL or length/mass (cm g-l)

Tissue density (g cm -3)

(% o f total root length

243 234 249 293 287 338 40

1240 1280 1430 1660 1750 2270 260

0.203 0.184 0.181 0.179 0.167 0.149 0.032

5.00 5.59 8.02 2.32 1.04 1.04 3.05

a From Eissenstat (1991). Pioneer roots are those roots >2 mm in diameter. Only roots in the ingrowth containers were measured. Roots were collected from 0 to 14 cm depth 19 weeks after installation of ingrowth containers beneath field trees in a Valencia orange rootstock trial (n = 8 trees of each rootstock). bMean of eight trees, 20-40 0.5-mm root segments per tree.

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Figure I The relationship of SRL with root growth rate into disturbed, root-free soil u n d e r the tree of six citrus rootstocks (top). Growth rate was d e t e r m i n e d by sampling ingrowth containers at 5, 10, and 19 weeks after disturbance. Ingrowth containers were installed to a d e p t h of 14 cm with the top flush with the soil surface. Specific root length was d e t e r m i n e d from the total root length divided by the root drywt at each sampling. (Bottom) T h e relationship of root length density with gravimetric soil water c o n t e n t 19 weeks after disturbance. Sampling was 8 days following a saturating rain. For both curves, symbols represent rootstock means _+ SE (n = 7-8), correlation coefficient (r) of rootstock means indicated n = 6. T h e rootstocks were sour orange (SO; Citrus aurantium), Swingle citrumelo (SC; Poncirus trifoliata • Citrus paradisi), Cleopatra mandarin (CM; Citrus reshni), rough lemon (RL; Citrusjambhiri), Volkamer lemon (VL; Citrus volkameriana), and trifoliate orange (TO; Poncirus trifoliata) b u d d e d to Valencia sweet orange. Trees were 13 years old (from Eissenstat, 1991).

large-diameter roots may grow slower and less readily proliferate in favorable soil patches but live longer than more fragile, small-diameter roots of higher water content.

VI. Exploiting Soil Heterogeneity Soils are not uniform. Nutrients and soil water are usually heterogeneously distributed in space and time. A plant may optimize C expenditure on the root system by withholding carbohydrates from roots unable to

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acquire water and nutrients and preferentially increasing the growth and activity of roots in locations where water and nutrients are most available, thus providing greater water or nutrient gain for the C expended on the root system. A. Preferential Carbon Allocation to Roots in Resource-Rich Patches

Proliferation of roots in localized patches rich in nutrients is a wellrecognized p h e n o m e n o n that occurs in most plants (e.g., Robinson, 1994). Furthermore, roots in these fertile patches often exhibit rapid shifts in their uptake kinetics, thus permitting higher specific rates of nutrient uptake at high supply rates than roots in the less fertile soil (Jackson et al., 1990). The greater root growth and activity in favorable nutrient patches presumably increases the efficiency of nutrient acquisition of the root system (nutrient acquired/carbon expended). Root growth is often greatest in wetter regions of the soil (e.g., Coutts, 1982). During a growing season with progressive drying of the soil surface layers, it is quite common for roots to exhibit staggered growth with roots near the surface exhibiting the most growth early in the season, whereas those in the deeper soil have the most growth activity later in the season (e.g., Fernandez and Caldwell, 1975). Other factors, such as soil temperature and proximity to the leaves, may also contribute to these root growth patterns. B. R e d u c e d Carbon Expenditure to Roots in Resource-Poor Soil

Reduction of maintenance costs of roots in the infertile or dry bulk soil can occur either by decreasing maintenance respiration or by shedding roots operating at lower efficiency. There is little direct evidence to support that maintenance respiration is lower for those roots of a plant located in less fertile soil patches. Although studies have shown that total respiration of roots supplied with moderate N is lower than those well supplied with N (Granato and Raper, 1989), this mainly reflects respiration associated with N uptake and assimilation and not higher maintenance respiration. Indirect evidence that maintenance respiration is also affected in highnutrient root axes, however, is indicated by greater Vmax(maximum rate of nutrient uptake per gram root at high nutrient supply) of roots in fertile than infertile patches (Jackson et al., 1990), which may cause higher rates of protein turnover and, thus, higher maintenance respiration than those roots in the less fertile bulk soil. Reduced maintenance costs have been more clearly associated with roots in dry soil. Palta and Nobel (1989) indicate that maintenance respiration of roots of desert succulents in dry soil is only about 13% of those under wet conditions. Greatly reduced respiration of roots exposed to dry soil has also been found in other desert perennial species (e.g., Holthausen and Caldwell, 1980; Sisson, 1989) and citrus (Espeleta and Eissenstat, 1997).

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Rather than reducing maintenance respiration of roots in less favorable soil, whole roots or the outer tissues (epidermis and cortex) of roots in unfavorable soil can be shed. Plant control of root longevity as a mechanism of optimizing the efficiency of the root system has not been well studied largely because of inadequate methods for tracking the fate of individual roots (Eissenstat and Yanai, 1997). Recent advances in viewing roots with clear access tubes (minirhizotrons) and extracting demographic information from videotapes with improved computer hardware and software are rapidly removing this obstacle to our understanding of root efficiency. Only a few studies have examined whether preferential shedding of roots occurs in response to nutrient heterogeneity, and these results are contradictory. Pregitzer et al. (1993) and Fahey and Hughes (1994) indicate that roots of northern hardwood species in low nutrient soil may die sooner than those in more fertile patches, but research with old-field herbaceous species indicated the opposite effect (Gross et al., 1993). Root shedding in dry portions of the soil profile has been more frequently reported. Root death in dry soil has been indicated in cotton (Klepper et al., 1973), timothy grass (Phleum pratense) (Molyneux and Davies, 1983), soybean (Huck et al., 1987), desert succulents (Huang and Nobel, 1992), Sitka spruce (Ferrier and Alexander, 1991), and big bluestem-dominated prairie (Hayes and Seastedt, 1987). Other species, however, such as corn (Taylor and Klepper, 1973; Stasovski and Peterson, 1991), wheat (Meyer et al., 1990), orchard grass (Dactylis glomerata) (Molyneux and Davies, 1983), perennial ryegrass (Lolium perenne) (Molyneux and Davies, 1983; Jupp and Newman, 1987), onion (Stasovski and Peterson, 1993), and citrus (Kosola and Eissenstat, 1994), apparently do not readily shed roots in dry surface soil, although detailed demographic information is often lacking. Partial shedding of root tissues, however, is common. In perennial rye grass (L. perenne), for example, the root cortex readily dies in response to drought while the stele remains alive with a functional pericycle, thus permitting the initiation of new laterals when the soil is rewetted (Jupp and Newman, 1987). Stasovski and Peterson (1991, 1993) have examined in detail the loss of tissues of onion and corn roots exposed to drought. Maintenance costs of a root with only a functional stele are undoubtedly less than those of a root with a full cortex.

C. Citrus Root Responses in Dry Surface Soil Carbon allocation, respiration, and death of surface roots of citrus have been studied in experiments in which deep roots have access to abundant soil moisture and in which shoots do not exhibit significant water stress. In a greenhouse study, seedlings of four citrus rootstocks that ranged widely in SRL were grown for 4 months in fine, sandy soil in a split-pot system divided into a top and bottom pot (Kosola and Eissenstat, 1994). After

6. Root Trade-offs

] 83

roots were well established in the bottom pot, water was withheld from the top pots of half of the plants. Plants were harvested every 2 weeks thereafter, 48 hr after labeling with 14C02~Contrary to our initial expectations, few roots died for any genotype, even after 60 days of localized soil drying. Carbon allocation to the roots, however, declined by about 80%. In a subsequent study, Espeleta and Eissenstat (1997) examined in the field the effects of dry surface soil on root mortality and root/soil respiration of Volkamer lemon seedlings and of bearing red grapefruit trees on Volkamer lemon rootstocks. Seedlings were grown adjacent to the grapefruit trees in wooden boxes buried in the soil in a similar split-pot system as described previously. Next to the seedling, a 5-mm-thick, woody lateral of the grapefruit tree was trained into a second split-pot system. Old fibrous roots were excised from the woody lateral prior to its placement into the pot system. Survivorship of new fine laterals emerging from the woody root was tracked on transparent windows on the side of the pot. Root/soil respiration from the surface of the top pot was also measured. Four weeks after withholding water, seedling root/soil respiration declined about 60% and tree r o o t / soil respiration declined about 70%. Seedlings continued to exhibit new root growth in the dry soil after this time so that it was impossible to partition total respiration into growth, maintenance, and ion uptake. For both seedlings and adult trees, few roots died even after 6 weeks of drought. For the adults, no new root growth in the top pot was observed after about 6 weeks of withholding water. After 15 weeks of drought, respiration was 0.11 mmol C g-1 day-a for roots of adults (Espeleta and Eissenstat, 1997) or about 4.4% of the maintenance respiration previously determined for seedlings in wet soil (Peng et al., 1993). Citrus evidently is a species that copes with dry surface soil not by shedding roots but by strongly downregulating root respiration. Because respiration rates and rates of ion uptake are downregulated in similar amounts (Espeleta and Eissenstat, 1997; Whaley, 1995), root efficiency (benefit/cost) is unchanged. Thus, simulation modeling of optimal life span predicts that citrus roots in dry surface soil should exhibit no difference in life span than those in wet soil (Eissenstat and Yanai, 1997). Moreover, it is not unreasonable that citrus exhibits less root death than many other species in response to dry surface soil because of their relatively high construction cost per unit root length compared to those of many other species.

VII. Root Architecture Root architecture, or the spatial configuration of a root system in the soil, has several components, including root distribution with depth or distance from the stem, root topology (root branching patterns), and some

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aspects of root morphology such as root diameter distribution (Lynch, 1995). There is no optimal root architecture for all environmental conditions. For example, many plants have their highest concentration of roots within a few cm of the soil surface, which often corresponds to the highest concentrations of N and P (Fitter, 1994). In deserts, however, the surface of exposed soil can exceed 70~ and become very dry, leading to little root development in the top 3-5 cm of soil (Rundel and Nobel, 1991). A. Root Distribution Native species vary widely in the depth and lateral spread of their root system and provide insights into the trade-offs of building a deep or laterally extensive root system. In the Mediterranean-type vegetation of Western Australia, D o d d e t al. (1984) excavated 551 root systems from 43 species of woody shrubs in sandy soil. Species that developed a root system characterized by deep taproots with few woody laterals or a dimorphic root system with deep taproots and extensive woody laterals only near the soil surface typically were plants that developed the largest shoots and were the slowest growing, longest lived, most drought tolerant and regenerated after fire mainly by resprouting. Short-lived, fast-growing species that regenerated mainly from seed generally had shallow roots and rarely invested in a distinct taproot. Trade-offs between a root system that produces many fine roots that readily increase root length in a given soil volume and a root system that rapidly increasing the total soil volume occupied can also be examined theoretically using architectural simulation models (Berntson, 1994). Berntson parameterized the model using P as the resource acquired and root parameters based on observations of common groundsel (Senecio vulgaris, a fast-growing annual dicot common to disturbed soils) grown at ambient and twice-ambient CO2 and two watering regimes. Root systems designed to occupy large soil volumes required larger average root diameters and were therefore less efficient in resource acquisition per unit soil volume than small root systems that exhibited more intensive growth around the stem. Thus, both empirical and theoretical studies indicate important tradeoffs between building deep roots for drought tolerance and building a root system that maximizes root length deployment for short-term nutrient gain. B. Root Topology

The costs and benefits of root systems of different topology have also been examined by model simulations (Fitter, 1991, 1994; Nielsen et al., 1994). One extreme topology is the branching pattern of a herringbone, or one that comprises a main axis and laterals only. At the other extreme is a dichotomous branching pattern in which each lateral bifurcates. For relatively mobile resources of high diffusivity (D > 10 - 7 c m 2 sec -1) interroot

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competition within a plant is significant and a herringbone topology tends to be the most efficient in terms of resource gain per unit C expended. Herringbone topologies, however, tend to have the smallest root length per unit root volume; consequently, as a first approximation, these root systems are the most expensive in terms of C to construct. This led Fitter (1991 ) to predict that herringbone roots should be favored in infertile soils, whereas dichotomous branched root systems should be more prevalent in habitats where soil resources are less important. Another area in which root architecture appears important is in the exploitation of resource-rich soil patches (Fitter, 1994). For example, roots that proliferate in patches tend to have a more dichotomous branching pattern with short, fine, laterals of high developmental order. Compared to coarse laterals in a herringbone topology, the fine roots of dichotomous branching likely are more precise in patch exploration and more readily develop a high a m o u n t of absorptive surface area for a limited C and nutrient investment. Fine, high-order laterals, however, are likely more ephemeral, less capable of nutrient and water transport, and extend less far from the parent root, leading to potentially more competition within the plant's root system than coarser laterals in a herringbone topology. Although these ideas regarding trade-offs associated with different root topologies are theoretically attractive, there is a notable lack of experimental evidence that supports that dichotomous branched roots of high-order turn over more rapidly and are less capable of transport than those with a herringbone topology.

C. Plant Breeding Root architecture can be influenced in plant breeding programs. Much variation exists in plant root systems that has thoroughly been reviewed elsewhere (O'Toole and Bland, 1987). Here, I will provide a few examples how differences in root architecture among crop cultivars may represent a trade-off between two types of environmental stresses. Jackson (1995) compared the root architecture of cultivated (Lactuca sativa) and wild (L. serriola) lettuce. She found no difference in the root branching patterns in the two species. She did find that the cultivated species produced more laterals in the top zone along the taproot (0-5 cm) and the wild lettuce produced more laterals in the 5- to 55-cm zone. This was assumed related to the intense selection of cultivated lettuce for rapid growth u n d e r conditions of frequent water and fertilizer application at the soil surface. Similarly, Bonser et al. (1996) found differences in root development near the soil surface among bean (Phaseolus vulgaris) genotypes. Root architecture was related to the growth angle of the basal roots. Genotypes that exhibited higher relative yield (low-P y i e l d / h i g h - P yield) in field trials also tended to have the most horizontally growing basal roots in seedlings. For some

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genotypes, shallow branching was a fixed trait; for others shallow branching occurred only under P deficiency. Under drought conditions, shallow branching likely would be a serious disadvantage. There has been extensive research aimed at selecting cultivars with deep rooting systems for drought resistance and, conversely, shallow rooted cultivars for soils of minimal water and nutrient stress (reviewed by O'Toole and Bland, 1987; Marcum et al., 1995). As previously discussed, evidence based on ecological comparisons of woody species and on model simulations suggests that it may be difficult to select for cultivars that develop deep roots but still exhibit high yields under nondrought conditions. This appears to be true, for example, in turf grasses. In a comparison of cultivars of buffalo grass, "Texoka" had the highest shoot dry weight and high root density at shallow depths but was less deeply rooted than many of the other cultivars (Marcum et al., 1995). D. Absorptive versus Structural Roots

One of the potential trade-offs of investing heavily in a root system that proliferates rapidly is retaining a root system capable of rapid extensive growth. Among citrus rootstocks, those that built relatively coarse fibrous roots produced more pioneer roots (operationally defined as new roots >2 mm in diameter), a developmentally distinct group of roots characterized by a pronounced root cap and rapid, indeterminate root extension with little immediate lateral root development (Table III). These roots become the principal roots forming the structural framework of the tree and typically are not readily infected by Phytophthora, mycorrhizal fungi, or nematodes. Because these roots undergo secondary growth and develop large metaxylem vessels, they accommodate a root system that occupies a larger soil volume with less axial resistance (resistance to water flow in the xylem) for water transport. The trade-offs of absorptive vs structural root development can be seen in rootstock performance. For example, trifoliate orange, the rootstock with the finest fibrous roots but fewest pioneer roots (Table III), is known for its ability to produce a small tree, especially on sandy soils (Castle, 1987). This rootstock is characterized by having shallow root systems with dense fibrous root systems but weak development of framework laterals, causing trees on this rootstock to be more susceptible to drought on sandy soils compared to other rootstocks.

VIII. Root Hydraulic Conductivity Root hydraulic conductivity (Lp; m s e c - 1 MPa -1) defines the intrinsic ability of roots to conduct water across a water potential gradient between

6. Root Trade-offs

] 87

the root surface and the xylem in the stem. Most of the resistance to water transport is normally associated with radial movement of water to the xylem of the fine roots (radial resistance; inverse of radial conductivity). Axial conductance (water movement in the xylem), however, may be an important factor affecting total water flow where xylem vessels are of small diameter such as in cereals (Greacen et al., 1976), where much of the xylem is immature and xylem cross-walls persist (St. Aubin et al., 1986), or where embolisms have occurred (Tyree and Cochard, 1994). Species may have evolved high root hydraulic conductivity where rates of water extraction influence competitive success (Eissenstat and Caldwell, 1988) or where plants must quickly take advantage of small rainfall events before significant soil evaporation occurs (Rundel and Nobel, 1991). Root hydraulic conductivity can be strongly influenced by root age. For example, rain roots of Agave deserti and Ferocactus acanthodes have approximately 5fold higher hydraulic conductivity than do 4-month-old roots and more than 15-fold higher hydraulic conductivity than do 2-year-old established roots. High hydraulic conductivity would be advantageous where an agricultural crop extracted water from the soil surface quickly following rains, thus requiring less weed management. A. Trade-offs in Axial Conductance

High root hydraulic conductivity is not necessarily advantageous for agricultural production in dryland conditions. In areas of the world where crops must grow to maturity on a finite, limited supply of water, it may be desirable to retard water use during early growth in order to retain available water for use during reproductive growth (Taylor, 1983). For example, in Australia a breeding program in wheat was established to decrease axial conductance by selecting for smaller xylem vessel diameters in seminal roots (Richards and Passioura, 1989). Field trials established the success of the technique; narrow vessel selections yielded between 3 and 11% more than unselected controls in the driest environments. Yield differences in wetter environments were largely insignificant. There is a positive correlation between vessel diameter and potential for cavitation of the water column in the vessel, resulting in an air embolism that greatly restricts water transport (Tyree and Ewers, 1991). Resistance of the xylem to cavitation is extremely important to drought resistance. Most research has been done with stems, but the same principles should apply to roots. For example, in a comparison of coexisting droughtdeciduous and evergreen woody species in a tropical dry forest, droughtdeciduous species maximized production during the wet season with higher water-transport efficiency; however, the high axial conductance led to the seasonal occurrence of embolisms (Sobrado, 1993). Evergreen species,

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on the other hand, had lower axial conductance but rarely developed xylem embolisms.

B. Radial Hydraulic Conductivity and SRL In citrus seedlings, we have found that SRL is positively correlated with root hydraulic conductivity (Fig. 2, top). Note that the citrus rootstock with the highest hydraulic conductivity, Poncirus trifoliata, is a deciduous species, whereas true Citrus rootstocks are evergreen; these are patterns consistent with those observed by Sobrado (1993) in tropical trees. The positive correlation of SRL with root hydraulic conductivity in citrus rootstocks can also be seen using three parent genotypes, trifoliate orange (P. trifoliata), Duncan grapefruit (Citrus paradisi), and ridge pineapple (Citrus sinensis), with two of their hybrids, Swingle citrumelo (P. trifoliata X C. paradisi) and Carrizo citrange (P. trifoliata X C. sinensis) (Fig. 2, bottom). Specific root

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F i g u r e 2 The relationship of SRL with root hydraulic conductivity of citrus seedlings. (Top) Original study using pressure chamber technique to pressurize entire root system and measure rates of xylem exudation from cut stem (data of Graham and Syvertsen, 1985; n = 12 seedlings per genotype _+ SE; correlation coefficient (r) of rootstock means indicated) (SO, sour orange; SC, Swingle citrumelo; CM, Cleopatra mandarin; CC, Carrizo citrange; TO, trifoliate orange). (Bottom) Follow-up study using similar techniques that compared two citrus hybrids, SC (Poncirus trifoliata X Citrus paradisi) and CC (P. trifoliata X Citrus sinensis), with their parental genotypes, Duncan grapefruit (DG; C. paradisi), Ridge pineapple sweet orange (RP; C. sinensis), and trifoliate orange (P. trifoliata) (]. Barker, D. Eissenstat, and J. Syvertsen, unpublished resuits).

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length was highest and mean root diameter and tissue density were lowest in trifoliate orange (Table III). Swingle citrumelo tended to exhibit both the SRL and hydraulic conductivity of its Duncan grapefruit parent, whereas Carrizo citrange exhibited more intermediate SRL and root hydraulic conductivity of its two parents, Ridge pineapple and trifoliate orange. Huang et al. (1995) examined the overall hydraulic conductivity, radial hydraulic conductivity, and axial conductance of individual primary and secondary roots of trifoliate orange, Swingle citrumelo, and sour orange. They found little difference in axial conductance but a higher radial hydraulic conductivity in trifoliate orange than in the other two rootstocks. These differences were linked to a smaller radius of the cortical tissue, lack of heavily lignified secondary walls in the hypodermis, and many more unsuberized passage cells in the secondary roots in trifoliate orange than in either Swingle citrumelo or sour orange.

IX. Root Herbivory and Root Defense Where plants allocate C and nutrients to defensive compounds that protect roots, there should be a cost in terms of reduced maximum potential growth rates in the absence of herbivory or parasitism. Thus, plant defense theories predict a negative relationship between defense and plant growth rate. This can include phenotypic and genotypic differences in defense allocation. Phenotypic responses in relation to resource supply are illustrated in tomato (Wilkens et al., 1996). At low levels of fertilization plant growth rates and production of defense compounds (rutin and chlorogenic acid) were low; at moderate rates of fertilization defense production, but not growth rate, was high; and at high rates of fertilization both defense production and growth rate were high (Wilkens et al., 1996). It is also hypothesized that species that have evolved in habitats of low resource supply should allocate more to defense and have longer-lived but slowergrowing tissues than those that evolved to compete in more productive habitats (Coley et al., 1985). Support for this hypothesis can be found in a comparative study of 41 neotropical tree species: slow-growing shadetolerant species had tougher, longer-lived leaves than fast-growing shadeintolerant species (Coley, 1988). Unfortunately, there has been very little direct investigation of the tradeoffs between root growth and activity and root defense. Most of the evidence is indirect. Typically, the fastest rates of mortality in minirhizotron and rhizotron studies are seen in the youngest, finest roots (Reid et al., 1993; Eissenstat and Yanai, 1997). Presumably, there is a "window of vulnerability" where new roots are highly susceptible to root-feeding organisms, as found in citrus with the fungal pathogen, Phytophthora nicotianae (Graham,

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1995). As roots age, they develop heavily suberized and lignified cell walls filled with tannins. This process can be accelerated under herbivore or pathogen pressure (Gerson, 1996). However, the accumulation of hydrophobic secondary compounds associated with aging or pathogens can also impede water and ion absorption, suggesting an important trade-off in root anatomy between absorption and defense (Rundel and Nobel, 1991; Peterson and Enstone, 1996). Other evidence of trade-offs between growth and defense comes from work on tissue density (Ryser, 1996), which will be discussed later. Plant tolerance of root-feeding organisms may not involve production of defense compounds but rather production of "surplus" roots so that root losses to herbivores/pathogens will have only a minimal impact on the aboveground growth. For example, in lettuce, a cultivar that is resistant to corky-root (Rhizomonas suberifaciens) disease has thinner roots than a susceptible cultivar, presumably allowing the former to outgrow the pathogen more easily (L. E. Jackson, unpublished data). This strategy, which should commonly occur in high-resource environments such as typical agricultural conditions, also represents a trade-off because in the absence of root-feeding organisms, the excessive root growth should limit maximum potential growth rates of the plant. Not all interactions of root herbivores or pathogens with roots should be considered trade-offs. Root morphological or architectural responses to pathogen infection may have little benefit to the plant, in terms of either defense or growth. For example, nematodes can cause gross alterations in root system morphology and architecture (Cohn et al., 1996). Pythium spp. can restrict root branching and growth (Larkin et al., 1995). In most cases, these root responses likely provide little benefit to the plant.

X. Mycorrhizae A. Costs and Benefits of Mycorrhizae The parallel between roots and leaves breaks down when mycorrhizal fungi are considered. Coarse roots may greatly increase their absorptive surface area by investing in the fine extramatrical hyphae of mycorrhizal fungi. Diameters of hyphal strands are typically only 2 - 4 / z m in diameter so that a root can greatly increase its absorptive surface area by forming a symbiosis with mycorrhizal fungi. The extent that a root invests in mycorrhizal fungi can also be considered from a cost/benefit perspective. Plants vary greatly in both the extent they are colonized by mycorrhizal fungi and their dependency on mycorrhizal fungi for P uptake and growth. Baylis (1975) first suggested that among vesicular-arbuscular mycorrhizal plants in low- to moderate@ soils, species that tend to produce large-

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diameter roots with few root hairs tend to be much more dependent on mycorrhizal fungi for P uptake and growth than those that produce fine roots with abundant root hairs. Subsequent studies have generally supported Baylis (Pope et al., 1983; Manjunath and Habte, 1991; Jasper and Davy, 1993), although plant P demand (Hall, 1975; Graham et al., 1991) and extent of root branching may also contribute to mycorrhizal dependency (Hetrick et al., 1992). As one might expect, species with coarse root systems (high mycorrhizal dependency) tend to be colonized faster or to a greater extent than those of low dependency (Reinhardt and Miller, 1990; Graham and Eissenstat, 1994). More mycorrhizal colonization is not a panacea for better plant nutrition or more favorable growth. For plants of similar P status, approximately 10-20% more current photosynthate is expended on mycorrhizal than nonmycorrhizal roots (see references in Peng et al., 1993). Thus, mycorrhizal fungi may represent an appreciable carbon drain for the plant if they are not providing a nutritional benefit. Many plants are effective at limiting colonization and carbon expenditure toward the mycorrhizal fungus under conditions in which the fungus can provide little benefit. Reduced mycorrhizal colonization is well documented in environments in which P availability is high or in which C availability is low (e.g., Son and Smith, 1988). Nonetheless, the somewhat limited mycorrhizal colonization of plants in high-P soils can still consume significant quantities of carbohydrates and lead to growth depressions. B. Citrus and Mycorrhizae The trade-offs of mycorrhizal colonization have been critically examined in citrus. Citrus roots are quite coarse (ca. 600-700/zm). Much of their root system is devoid of root hairs. Where root hairs are present, they tend to be very short and extend less than 100/zm, which would not tend to expand appreciably the root's depletion zone (Fig. 3). Consequently, citrus plants are generally considered highly dependent on mycorrhizal fungi in low- to moderate-P soil. For example, P inflow (fmol cm -1 sec -1) was more than three times higher in mycorrhizal than nonmycorrhizal sour orange seedlings at low-P supply (Eissenstat et al., 1993). At high-P supply, however, mycorrhizal fungi may provide little or no P benefit. For example, Peng et al. (1993) grew mycorrhizal and nonmycorrhizal lemon seedlings at lowand high-P supply for 90 days. At the end of the experiment, mycorrhizal plants were nearly twice the dry weight of nonmycorrhizal plants at low-P supply. However, at high-P supply, mycorrhizal plants were 8% smaller than nonmycorrhizal plants. They found that the mycorrhizal fungus, Glomus intraradices, established numerous lipid-rich vesicles in the roots of the lemon seedlings, causing increased root fatty acid content and increased root construction cost (g glucose/g dry wt). Not surprisingly, fatty acid

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Figure 3 Scanning electron micrograph of root hairs of the citrus rootstock genotype, Cleopatra mandarin. Samples were fixed in glutaraldehyde and dehydrated in ethanol series, then critical-point dried with CO2 and sputter coated with 80:20 gold : palladium for 90 sec. Microscopy was performed with a Hitachi Model $530 at 200X (micrograph kindly provided by Richard Crawford).

content and root construction costs were highly correlated (Fig. 4). Among high-P plants, mycorrhizal colonization increased root biomass allocation compared to nonmycorrhizal plants. At 52 days after transplanting, high-P nonmycorrhizal plants had 20% higher daily specific carbon gain (mmol g-1 day-l) than the mycorrhizal plant because of 37% higher rootsoil respiration in the mycorrhizal plants. Of the 37% higher root-soil respiration, 10% was directly attributable to building lipid-rich roots, 51% to greater mycorrhizal root biomass allocation, and the remaining 39% to maintenance of the fungal tissue in the roots and growth and maintenance of the extramatrical hyphae. Although mycorrhizal costs probably would decline as the roots aged, the results nonetheless illustrate the trade-offs of mycorrhizal colonization depending on P supply. In soils in which P availability is a problem, there is little doubt that citrus benefits from being mycorrhizal. In contrast, under intensive management conditions in which water and nutrients are supplied in abundance (as is common in Florida citrus production), mycorrhizal fungi should not be considered a symbiont but a weak parasite that may influence maximum potential growth rates and

6. Root Trade-offs

1.48 "~O~ ~.~~ 1.441.40 r2= 0.92 (n=l~

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.m

0 ~ 1.32 ~

~

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0 ~" NM5 IT' ~ ~ ~.~4t ~ I I I I I I 10 20 30 40 50 60 70 Total fatty acid (relative units) Figure 4 Relationshipof construction cost of fibrous roots with their relative total fatty acid content in nonmycorrhizal (NM) and mycorrhizal (M) Volkamer lemon seedlings colonized by Glomus intraradices at low- (1) and high-P (5) supply (redrawn from Figure 5 in Peng, S., Eissenstat, D. M., Graham, J. H., Williams, K., and Hodge, N. C. (1993). Growth depression in mycorrhizal citrus at high-phosphorus supply. Plant PhysioL 101, 1063-1071. 9 American Society of Plant Physiologists).

yield ( G r a h a m a n d Eissenstat, 1994). T h e costs of trying to limit mycorrhizal fungal infection, however, would likely far outweigh the potential benefits associated with increased production.

XI. Root Life Span As in leaves, there is a wide range in m e d i a n root life span, from about 14 days in apple a n d strawberry to m o r e than 2 years in some pine forests (Eissenstat a n d Yanai, 1997). Simulation m o d e l i n g can help identify factors that may influence optimal root life span. Root efficiency can be defined as the total resource benefit acquired by a root over its lifetime divided by the total c a r b o n e x p e n d e d on the root (Yanai et al., 1995). T h e carbon cost would include the initial cost of root construction a n d the lifetime cost of root m a i n t e n a n c e respiration, which could also include such factors as carbon e x p e n d e d on mycorrhizal fungi a n d on root exudates. Uptake for solutes would include the uptake kinetics a n d water influx of the root, SRL, a n d root diameter, as well as soil factors affecting solute diffusion a n d mass flow to the root. Optimal root life span in this context would be to retain a root until its lifetime efficiency is maximized. Roots with high rates of m a i n t e n a n c e respiration would be expected to be shed sooner than roots with low m a i n t e n a n c e respiration. Aspects of root efficiency a n d root life span have b e e n m o r e thoroughly reviewed elsewhere (Eissenstat a n d Yanai, 1997).

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There has been little experimental investigation of the trade-offs in root form and function that affect root life span. An exception is a study of perennial grasses, in which there is evidence of a link between root construction and root life span (Ryser, 1996). In a c o m m o n garden experiment, root life span and root density were contrasted in five grass species (Arrhenatherum elatuis, Dactylis glomerata, Holcus lanatus, Bromus erectus, and Festuca ovina), which are found in a range of habitats that differed widely in nutrient availability. Tissue density of roots ranged from 0.17 to 0.28 g cm -~ with the species from the sites with the lowest nutrient availability having the highest tissue density. These species grew slowest and had the longest root longevity, as indicated by the percentage of dead root to total root length after approximately 1.5 years of growth. The relationships of tissue density, growth, and life span of leaves were similar to those in roots. Ryser convincingly argues that short organ life span should lead to greater nutrient losses, which in nutrient-poor habitats would be more disadvantageous than greater acquisition capacity. One would predict that citrus roots with low SRL should live longer than those with high SRL; otherwise, it is not clear what would be the advantage of building a root that had more dry mass per unit length. However, minirhizotron investigations in a citrus rootstock trial have indicated that median life spans of trifoliate orange roots (90 days) are similar to those of Swingle citrumelo (99 days) and sour orange (90 days) (roots born between April 1992 and December 1992; n = 565-1107; D. Eissenstat, unpublished data), even though SRL varies by more than 80% (Table III). Root constructions costs per unit mass (g glucose g-1 dry wt) of these rootstocks are very similar (D. Eissenstat, unpublished data). Other costs not measured, such as root respiration and expenditure on mycorrhizal fungi, may be needed to better account for rootstock differences in life span. The factor most linked to life span in these rootstocks was resistance to Phytophthora infection (Kosola et al., 1995), although the energetic cost of this resistance has not been quantified.

Xll. Summary and Conclusions Root construction represents a series of trade-offs. Plants that allocate more carbon on the root system and less on shoot growth normally have slower relative growth rates. Plants that build mostly fine roots may grow faster initially but do not lay down the belowground framework to support a large plant with access to deep water. Roots of high hydraulic conductivity may be more susceptible to embolism. Roots constructed for maximizing short-term benefits in water and nutrient absorption, such as small diameter, low tissue density (high water content), and high capacity to proliferate

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in favorable soil patches, may have a higher maintenance respiration rate and a shorter life span. These traits may be typical of roots in annual crops and fast-growing woody species of fertile soils. On the other hand, roots can be constructed to be well defended from belowground herbivores, pathogens, and soil desiccation, but at the costs of slower growth rates, higher carbon investment per unit length, lower specific absorption rates, and less ability to proliferate in favorable soil patches. Coarse fibrous roots may also invest more heavily in the mycorrhizal symbiosis, which can also represent an appreciable cost. The concept that optimal root design represents a compromise of competing root functions needs to be more formally included in the selection and management of crops. This can be seen, for example, in the lack of drought tolerance in trifoliate orange because of its lack of deep structural roots and preponderance of fine, absorptive roots that readily proliferate and exhibit high hydraulic conductivity. Breeding for more drought tolerance in crops, however, may mean selecting for plants that invest more in deep roots or roots of smaller xylem vessel diameters but that exhibit lower yield under nondrought conditions. Root systems of crops intended for agricultural systems with low inputs of fertilizer, irrigation, and pesticides may have additional costs that would not be advantageous for crops under intensive management conditions.

Acknowledgments Some of this work was supported by Grant NRICGP-94-37107-1024 from the United States Department of Agriculture and by Grants BSR-911824 and IBN-956050 from the National Science Foundation. Helpful comments were provided by David Bryla, Louise Jackson, Jonathan Lynch, and two anonymous reviewers.

References Amthor, J. S. (1984). The role of maintenance respiration in plant growth. Plant Cell Enviorn. 7, 561-569. Amthor, J. S., Mitchell, R. J., Runion, G. B., Rogers, H. H., Prior, S. A., and Wood, C. W. (1994). Energy content, construction cost and phytomass accumulation of Glycine max (1.) Merr. and Sorghum bicolor (L.) Moench grown in elevated CO2 in the field. New Phytol. 128, 443-450. Barber, S. A., and Silberbush, M. (1984). Plant root morphology and nutrient uptake. In "Roots, Nutrient and Water Influx, and Plant Growth" (S. A. Barber and D. R. Bouldin, eds.), pp. 65-87. American Society of Agronomy, Madison, WI. Baylis, G. T. S. (1975). The magnolioid mycorrhiza and mycotrophy in root systems derived from it. In "Endomycorrhizas" (F. E. Sanders, B. Mosse, and P. B. Tinker, eds.), pp. 373-389. Academic Press, New York.

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Berntson, G. M. (1994). Modelling root architecture: Are there tradeoffs between efficiency and potential of resource acquisition? New Phytol. 127, 483-493. Bloom, A.J., Chapin, F. S., III, and Mooney, H. A. (1985). Resource limitation in plants: An economic analogy. Annu. Rev. Ecol. Syst. 16, 363-392. Bonser, A. M., Lynch, J., and Snapp, S. (1996). Effect of phosphorus deficiency on growth angle of basal roots in Phaseolus vulgaris. New Phytol. 132, 281-288. Caldwell, M. M. (1979). Root structure: The considerable cost of belowground function. In "Topics in Plant Population Biology" (O. T. Solbrig, S. Jain, G. B. Johnson, and P. H. Raven, eds.), pp. 408-427. Columbia Univ. Press, New York. Caldwell, M. M. (1987). Competition between root systems in natural communities. In "Root Development and Function" (P.J. Gregory, J. V. Lake, and D. A. Rose, eds.), pp. 167-185. Cambridge Univ. Press, New York. Castle, W. S. (1987). Citrus rootstocks. In "Rootstocks for Fruit Crops" (R. C. Rom and R. F. Carlson, eds.), pp. 361-397. Wiley, New York. Chapin, F. S., III (1987). Plant response to multiple environmental factors. BioScience37, 49-57. Chapin, F. S., III (1989). The cost of tundra plant structures: Evaluation of concepts and currencies. Am. Nat. 133, 1-19. Chapin, F. S., III (1993). Evolution of suites of traits in response to environmental stress. Am. Nat. 142, $78-$92. Cohn, E., Koltai, H., Sharon, E., and Spiegel, Y. (1996). Root-nematode interactions: Recognition and pathogenicity. In "Plant Roots: The Hidden Half" (Y. Waisel, A. Eshel, and U. Kafkafi, eds.), 2nd ed., pp. 797-809. Dekker, New York. Coley, P. D. (1988). Effects of plant growth rate and leaf lifetime on the amount and type of anti-herbivore defense. Oecologia 74, 531-536. Coley, P. D., Bryant, J. P., and Chapin, F. S., III (1985). Resource availability and plant antiherbivore defense. Science 230, 895-899. Coutts, M. P. (1982). Growth of Sitka spruce seedlings with roots divided between soils of unequal matric potential. New Phytol. 92, 49-61. Dodd, J., Heddle, E. M., Pate, J. S., and Dixon, K. W. (1984). Roofing patterns of sandplain plants and their functional significance. In "Kwongan: Plant Life of the Sandplain" (J. s. Pate and J. S. Beard, eds.), pp. 146-177. Univ. of Western Australia Press, Nedlands. Eissenstat, D. M. (1991). On the relationship between specific root length and the rate of root proliferation: A field study using citrus rootstocks. New Phytol. 118, 63-68. Eissenstat, D. M. (1992). Costs and benefits of constructing roots of small diameter. J. Plant Nutr. 15, 763-782. Eissenstat, D. M., and Caldwell, M. M. (1988). Competitive ability is linked to rates of water extraction: A field study of two aridland tussock grasses. Oecologia 75, 1-7. Eissenstat, D. M., and Van Rees, BL C.J. (1994). The growth and function of pine roots. Ecol. Bull. 43, 76-91. Eissenstat, D. M., andYanai, R. D. (1997). The ecology of root lifespan. Adv. Ecol. Res., 27, 1-60. Eissenstat, D. M., Graham,J. H., Syvertsen,J. P., and Drouillard, D. L. (1993). Carbon economy of sour orange in relation to mycorrhizal colonization and phosphorus status. Ann. Bot. 71, 1-10. Espeleta, J. F., and Eissenstat, D. M. (1997). Effects of tree juvenility on citrus fine root mortality in dry surface soil. Tree Physiol., in press. Fahey, T.J., and Hughes, J. W. (1994). Fine root dynamics in a northern hardwood forest ecosystem, Hubbard Brook Experimental Forest, NH. J. Ecol. 82, 533-548. Fernandez, O. A., and Caldwell, M. M. (1975). Phenology and dynamics of root growth of three cool semi-desert shrubs under field conditions. J. Ecol. 63, 703-714. Ferrier, R. C., and Alexander, I.J. (1991). Internal redistribution in N in Sitka spruce seedlings with partly droughted root systems. For. Sci. 37, 860-870.

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Fitter, A. H. (1991). Characteristics and functions of root systems. In "Plant Roots: The Hidden Half" (Y. Waisel, A. Eshel, and U. Kafkafi, eds.), pp. 3-26. Dekker, New York. Fitter, A. H. (1994). Architecture and biomass allocation as components of the plastic response of root systems to soil heterogeneity. In "Exploitation of Environmental Heterogeneity of Plants: Ecophysiological Processes Above- and Belowground" (M. M. Caldwell and R. W. Pearcy, eds.), pp. 305-323, Academic Press, New York. Fogel, R. (1985). Roots as primary producers in below-ground ecosystems. In "Ecological Interactions in Soil" (A. H. Fitter, D. Atkinson, D. J. Read, and M. Usher, eds.), Spec. Publ. Ser. of the British Ecological Society No. 4, pp. 23-36. Blackwell, Oxford. Garnier, E., and Laurent, G. (1994). Leaf anatomy, specific mass and water content in congeneric annual and perennial grass species. New Phytol. 128, 725-736. Gerson, U. (1996). Arthropod root pests. In "Plant Roots: The Hidden Half" (Y. Waisel, A. Eshel, and U. Kafkafi, eds.), 2nd ed., pp. 797-809. Dekker, New York. Graham, J. H. (1995). Root regeneration and tolerance of citrus rootstocks to root rot caused by Phytophthora nicotianae. Phytopathology 85, 111-117. Graham, J. H., and Eissenstat, D. M. (1994). Host genotype and the formation and function of VA mycorrhizae. Plant Soil 159, 179-185. Graham, J. H., and Syvertsen, J. P. (1985). Host determinants of mycorrhizal dependency of citrus rootstock seedlings. New Phytol. 101,667-676. Graham, J. H., Eissenstat, D. M., and Drouillard, D. L. (1991). On the relationship between a plant's mycorrhizal dependency and rate of vesicular-arbuscular mycorrhizal colonization. Funct. Ecol. 5, 773-779. Granato, T. C., and Raper, D.,Jr. (1989). Proliferation of maize (Zea mays L.) roots in response to localized supply of nitrate. J. Exp. Bot. 40, 263-275. Greacen, E. L., Posana, P., and Barley, K. P. (1976). Resistance to water flow in the roots of cereals. In "Water and Plant Life. Problems and Modern Approaches" (O. L. Lange, L. Kappen, and E.-D. Schulze, eds.), pp. 86-100. Springer-Verlag, Berlin. Grime, J. P. (1994). The role of plasticity in exploiting environmental heterogeneity. In "Exploitation of Environmental Heterogeneity of Plants: Ecophysiological Processes Aboveand Belowground" (M. M. Caldwell and R. W. Pearcy, eds.), pp. 1-20. Academic Press, New York. Gross, K. L., Peters, A., and Pregitzer, K. S. (1993). Fine root growth and demographic responses to nutrient patches in four old-field plant species. Oecologia 95, 61-64. Hall, I. R. (1975). Endomycorrhizas of Meterosideros umbeUata and Weinmannia racemosa. New ZealandJ. Bot. 13, 463-472. Harley, J. L., and Smith, S. E. (1983). "Mycorrhizal Symbiosis." Academic Press, New York. Hayes, D. C., and Seastedt, T. R. (1987). Root dynamics of tallgrass prairie in wet and dry years. Can. J. Bot. 65, 787-791. Hetrick, B. A. D., Wilson, G. W. T., and Todd, T. C. (1992). Relationship of mycorrhizal symbiosis, rooting strategy, and phenology among tallgrass prairie forbs. Can. J. Bot. 70, 1521-1528. Holthausen, R. S., and Caldwell, M. M. (1980). Seasonal dynamics of root system respiration in Atriplex confertifolia. Plant Soil 55, 307-317. Huang, B., and Nobel, P. S. (1992). Hydraulic conductivity and anatomy for lateral roots of Agave deserti during root growth and drought-induced abscission. J. Exp. Bot. 43, 1441-1449. Huang, B., Eissenstat, D. M., and Achor, D. (1995). Root hydraulic conductivity in relation to its morphological and anatomical characteristics for citrus rootstocks. International Symposium: Dynamics of Physiological Processes in Roots, October 8-12, Ithaca, NY. [Abstract] Huck, M. G., Hoogenboom, G., and Peterson, C. M. (1987). Soybean root senescence under drought stress. In "Minirhizotron Observation Tubes: Methods and Applications for Mea-

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suring Rhizosphere Dynamics" (H. M. Taylor, ed.), ASA Spec. Publ. No. 50, pp. 109-121. Agronomy Society of America, Madison, WI. Ingestad, T. and Agren, G. I. (1991). The influence of plant nutrition on biomass allocation. Ecol. Appl. 1, 168-174. Jackson, L. E. (1995). Root architecture in cultivated and wild lettuce (Lactuca spp.). Plant Cell Environ. 18, 885-894. Jackson, R. B., Manwaring, J. H., and Caldwell, M. M. (1990). Rapid physiological adjustment of roots to localized soil enrichment. Nature (London) 344, 58-60. Jasper, D. A., and Davy, J. A. (1993). Root characteristics of native plant species in relation to the benefit of mycorrhizal colonization for phosphorus uptake. Plant Soil 155/156,281-284. Jupp, A. P., and Newman, E. I. (1987). Morphological and anatomical effects of severe drought on the roots of Lolium perenne L. New Phytol. 105, 393-402. Klepper, B., Taylor, H. M., Huck, M. G., and Fiscus, E. L. (1973). Water relations and growth of cotton in drying soils. Agron. J. 54, 307-310. Kosola, K. R., and Eissenstat, D. M. (1994). The fate of citrus seedlings in dry soil. J. Exp. Bot. 45, 1639-1645. Kosola, K. R., Eissenstat, D. M., and Graham, J. H. (1995). Root demography of mature citrus trees: The influence of Phytophthora nicotianae. Plant Soil 171,283-288. Larkin, R. P., English, J. T., and Mihail, J. D. (1995). Effects of infection by Pithium spp. on root system morphology of alfalfa seedlings. Phytophathology 85, 430-435. Lynch, J. (1995). Root architecture and plant productivity. Plant Physiol. 109, 7-13. Manjunath, A., and Habte, M. (1991). Root morphological characteristics of host species having distinct mycorrhizal dependency. Can. J. Bot. 69, 671-676. Marcum, K. B., Engelke, M. C., and Morton, S.J. (1995). Roofing characteristics of buffalograsses grown in flexible plastic tubes. HortScience 30, 1390-1392. Meyer, W. S., Tan, C. S., Barrs, H. D., and Smith, R. C. G. (1990). Root growth and water uptake by wheat during drying of undisturbed and repacked soil in drainage lysimeters. Aust. J. Agric. Res. 41,253-265. Molyneux, D. E., and Davies, W. J. (1983). Roofing patterns and water relations of three pasture grasses growing in drying soil. Oecologia 58, 220-224. Nielsen, K. L., Lynch, J. P., Jablokow, A. G., and Curtis, P. S. (1994). Carbon cost of root systems: An architectural approach. Plant Soil 165, 161-169. O'Toole, J. C., and Bland, W. L. (1987). Genotypic variation in crop plant root systems. Adv. Agron. 41, 91-145. Palm, J. A., and Nobel, P. S. (1989). Influences of water status, temperature, and root age on daily patterns of root respiration of two cactus species. Ann. Bot. 63, 651-662. Peng, S. B., Eissenstat, D. M., Graham, J. H., Williams, K., and Hodge, N. C. (1993). Growth depression in mycorrhizal citrus at high-phosphorus supply: Analysis of carbon costs. Plant Physiol. 101, 1063-1071. Peterson, C. A., and Enstone, D. E. (1996). Functions of passage cells in the endodermis and exodermis of roots. Physiol. Plant. 97, 592-598. Poorter, H., and Remkes, C. (1990). Leaf area ratio and net assimilation rate of 24 wild species differing in relative growth rate. Oecologia 83, 553-559. Pope, P. E., Chaney, W. R., Rhodes, J. D., and Woodhead, S. H. (1983). The mycorrhizal dependency of four hardwood tree species. Can. J. Bot. 61,412-417. Pregitzer, K. S., Hendrick, R. L., and Fogel, R. (1993). The demography of fine roots in response to patches of water and nitrogen. New Phytol. 125, 575-580. Reich, P. B., Walters, M. B., and Ellsworth, D. S. (1992). Leaf life-span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol. Monogr. 62, 365-392. Reid, J. B., Sorensen, I., and Petrie, R. A. (1993). Root demography in kiwifruit (Actinidia deliciosa). Plant Cell Environ. 16, 949-957.

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II Biotic Interactions and Processes

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7 The Use of Biodiversity to Restrict Plant Diseases and Some Consequences for Farmers and Society Maria R. Finckh and Martin S. Wolfe

I. Introduction Until the past few hundred years, agriculture developed on the basis of biodiverse systems, with greater amounts of both interspecific and intraspecific variation than are seen today in the developed world. Some of that diversity was disadvantageous (barberry and buckthorn around wheat and oat fields) and some was advantageous, leading to the development of many useful systems of plant production that helped to constrain plant diseases (Thurston, 1992) and that are still evident in a number of indigenous systems, mostly in tropical regions. One universal advantage was almost certainly compensation: By producing a wide range of crops and animals, and by using "naturally" occurring materials, farm operations were buffered against the ravages of individual pathogens and pests. During the past 300 years or so, correlated with the increase in the growth of the world's human population, there has been a massive increase in food production brought about by many factors including the development of plant breeding and production-orientated intensification of agriculture. This was boosted particularly in the 20th century by governmental policies aimed at increasing self-sufficiency in food production at any cost. A major development, seen all over the developed world, was specialization among few crops and the consequent massive monoculture of, for example, small and coarse grain cereals. Recently, as experience with monoculture has developed, we now see more clearly some of the major disadvantages that follow, for example, in Ecology in Agriculture

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the way in which this encourages massive and rapid development of particular diseases, pests, and weeds. There are two general solutions to the problem. The first is to improve the monoculture technology by breeding more durably resistant crop varieties and by relying on pesticides. The second is to develop rationally the use of the biodiversity that is already available. In our view, this latter approach can help not only to deal with disease, pest, and weed problems but also provide a new framework for agricultural production that is more sustainable than the systems currently practiced in the developed world. A remarkable confirmation of the possible positive correlation between biodiversity, on the one hand, and production and sustainability, on the other hand, has been demonstrated by Tilman et al. (1996) for a natural ecosystem. Genetic diversity for disease resistance has been advocated and developed as a means to control plant diseases for more than half a century by plant pathologists and breeders (e.g., Browning et al., 1969; Jensen, 1952, 1988; Harlan, 1972; Stevens, 1942) and the effects of diversity on disease have been demonstrated in a large n u m b e r of studies in numerous c r o p - p a t h o g e n systems. Our aim in this chapter is to provide an overview of these developments and to try to indicate in a more general social context some of the advantages and constraints in such an approach. We also comment on some of the difficulties involved in changing toward exploitation of biodiversity because of the resistance to change that has already become built into the large-scale specialist approach.

II. The Pathologist's View A. The Status Quo: Monoculture The massive increase in the use of a few crop species (crop monoculture) over the past few hundred years and reliance on an often narrow genetic base for the varieties has led to many severe and chronic disease problems, well known for cereals but also for many other crops (Adams et al., 1971; Browning et al., 1969; Harlan, 1972; Ullstrup, 1972). Crop monoculture was established first in cereals and then developed widely. Within each cereal monoculture, and later in other crops, there developed further the monoculture of individual varieties and then, on a larger scale, the monoculture of individual resistance genes (we may refer, therefore, to crop monoculture, variety monoculture, and resistance monoculture; some degree of crop monoculture is now inevitable because of the high demand for wheat, rice, and maize; variety or resistance monoculture is not inevitable). Genetic uniformity has been identified as the cause of many devastating epidemics, for example, the outbreak of late blight (caused by Phytophthora

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infestans) in 1845-1847, which destroyed the Irish potato crop and led to the starvation of 2 million people and the mass emigration of another 2 million from Ireland (Adams et al., 1971; Harlan, 1972). The pathogen spread throughout Europe in the following years, destroying much of the crop, because the potato varieties at the time were uniformly susceptible to the disease because there had been no previous selection for resistance. Uniform susceptibility of coffee (C0ffea arabica) to rust (caused by Hemileia vastatrix) led to massive losses in coffee production in Sri Lanka in the 1870s and to widespread epidemics in South America following the introduction of the rust into Brazil in 1970 (Schumann, 1991). In 1970, southern corn leaf blight (caused by Cochliobolus carbonum) destroyed much of the U.S. corn crop causing an economic loss of several billion dollars (Ullstrup, 1972). Early breeding for resistance relied heavily on the use of simply inherited race-specific resistance (Johnson, 1961). Hopes were high that the use of such resistance would end devastating epidemics, but they were soon shattered. Often, new pathogen races were selected that were virulent on previously resistant varieties soon after the varieties became popular and occupied large areas (Adams et al., 1971; Harlan, 1972;Johnson, 1961; Van der Plank, 1963), resulting in what has been referred to as "boom and bust cycles" (e.g., Wolfe, 1973). For example, it took an average of 2 or 3 years for the powdery mildew pathogen (Erysiphe graminis f.sp. hordei) to overcome previously highly effective resistances in barley once they were introduced on a large scale (Brown et al., 1997) (Fig. 1). Similar boom and bust cycles could be followed in the rice-rice bacterial blight (caused by Xanthomonas oryzaepv, oryzae) system (Mew et al., 1992) and the wheat-stripe rust (caused by Puccinia striiformis) system (Danial et al., 1994; Wellings and McIntosh, 1990). The epidemics that "bust" popular varieties are usually due to huge increases in population size of the relevant pathogen genotypes, providing a source population from which inoculum of virulent races migrates to new regions. In intensive agriculture, the current method of avoiding disaster in the bust phase is the "replacement strategy": As one resistance is overcome, it is replaced by another (Duvick, 1977). This has considerable disadvantages for the farmer and for society in terms of sustainability (cost of seed, difficulty of keeping up to date, problems of marketing, loss of valuable genetic resources, and environmental and economic costs of fungicide use during the changeover period while pesticides are used). The main alternative within monocultures is to improve durability of resistance. Durable resistance is defined as "resistance that remains effective in a cultivar that is widely grown for a long period of time in an environment favorable to the disease" (Johnson, 1993, p. 284). Note that both the test for and exploitation of durability usually refer to large-scale monoculture. One

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Maria R. Finckh and Martin S. Wolfe

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named were the first in the United Kingdom to carry the resistance genes Mlal2, Mla7 + Mlkl, Ml(Ab), Mla9, or Mlal3; Triumph and Kym also had Mla7 and Mlkl, respectively. The powdery mildew resistance ratings are those given in Recommended Varieties of Cereals by the National Institute of Agricultural Botany. 9 or 8, good resistance; 7 or 6, moderate resistance; 5 or 4, moderate susceptibility; 3, 2, or 1, high susceptibility (from Brown et al., 1997).

strategy that is thought to improve durability is by the use of resistance gene combinations that reduce the probability of occurrence of a new virulent pathogen genotype (see Section III,A for discussion).

B. Host-Pathogen Coevolution An aspect not fully considered in the "monoculture with replacement" strategy is the form of eoevolution that occurs between host and pathogen. We define coevolution as the partial coordination of nonmixing gene pools through biotic selection caused by competition, predation, or parasitism (Ehrlich and Raven, 1964; Futuyma and Slatkin, 1983; Harper, 1982; Thompson, 1982); this depends on the availability of relevant genetic variation. As a host population develops, its changing structure results from interactions among the host components, which can strongly influence the structure and dynamics of the pathogen population. Simultaneously, the host interactions can be influenced by the development of the pathogen population (the epidemic), which may have differential effects on the host components, affecting their final reproductive output and thus fitness, where we define fimess according to Harper (1977, p. 770): "The fimess of an

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organism is measured by the descendents that it leaves, measured over a number of generations." To understand coevolutionary interactions among hosts and their pathogens, it is important to keep in mind the following: (i) Although host plants do not depend on the existence of their pathogens for survival, many pathogens, especially fungi and viruses, cannot survive a n d / o r reproduce for long in the absence of their hosts. Thus, we may expect pathogen populations to respond more strongly to their host's genetic composition than vice versa; (ii) pathogens differ in the degree of their dependence on specific hosts, i.e., there is variation in host specificity; (iii) coevolutionary interactions depend strongly on the balance among the reproductive systems that are involved [e.g., sexual, asexual, and parasexual (i.e., recombination without meiosis)], alternate hosts, and generation time, which is generally much shorter for pathogens than for their hosts; (iv) the scale at which host and pathogen populations interact, which may have major effects on the outcome. For example, relative to the mode of dispersal of the pathogen, small separated fields may act as islands, whereas large-scale monoculture tends to join the islands (see Chapter 8, this volume) making migration for the pathogen easier, lessening population subdivision, and enhancing regional epidemics. For example, the use of different stem rust (caused by Puccinia graminis f.sp. tritici) resistance genes in wheat breeding programs in North America greatly affected the population dynamics of the rust. Overwintering inoculum from the South was selected to attack a set of resistance genes different from those used in the central and northern regions that depend on southern inoculum for the start of new epidemics each year. The southern inoculum first had to be reselected on the central and later on the northern varieties, greatly slowing down overall epidemic development (Knott, 1972) Compared to natural systems, coevolution in agricultural systems differs principally in relation to the factors affecting "fitness" over generations of the host. In agriculture, humans decide which variety to grow on what scale and where. Although these decisions are influenced by the environmental conditions (including disease pressure), the environment can be ameliorated, for example, by the use of soil amendments and pesticides. No such interference happens in natural ecosystems and a wider range of factors may influence significantly the life history of host plants (see Section II,B,2).

1. Host-Pathogen Coevolution in Agricultural Ecosystems The direct, strong, and mutual influence of host and pathogen genetic composition has long been recognized in agroecosystems (e.g., Flor, 1953; Harlan, 1976;Johnson, 1961; Johnson et al., 1967; Leonard and Czochor, 1980; McDonald et al., 1989b; Stakman, 1947; Stevens, 1942; Wolfe, 1973; Wolfe and Barrett, 1977,

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1980). Most of these interactions are three sided, involving host, pathogen, and humans. In some cases, in which no conscious selection is exerted on the crop by humans, the process is more truly two sided. Flor (1953) was the first to uncover the large effects that humans can have in driving the coevolution of hosts and pathogens. He revealed the close interrelation between the resistance genes of flax (Linum usitatissimum) and the virulence genes of Melampsora lini (causing flax rust). From 20 years of race surveys, he found that the prevalence of different races of the rust was determined largely by the resistances in the common flax varieties. Based on the analysis of many crosses, Flor (1956) then hypothesized that during the coevolution of the rust and the host, complementary genic systems in host and pathogen had evolved, and that for each gene controlling resistance/susceptibility in the host there is a corresponding gene controlling avirulence/virulence in the pathogen. This was termed the gene-for-gene hypothesis. The resistance genes in the host were often found to be dominant multiple alleles involving a few loci, whereas the virulence genes in the rust were recessive and not allelic. Johnson (1961) and Johnson et al. (1967) described the "man-guided evolution in plant rusts." The cereal rusts had changed their racial composition from a large n u m b e r of "standard races" in earlier epidemics in central north America toward one or a group of related races that could overcome the predominantly used resistance genes. In a more detailed study covering 56 years of data, Kolmer (1991) found a close correlation between host and pathogen genetic composition in the wheat (Triticum aestivum)-wheat leaf rust (caused by Puccinia recondita f.sp. tritici) system in Canada. With the change to the use of markedly distinct wheat varieties in the eastern and western regions, the rust population became subdivided. The first resistance gene used consciously in barley (Hordeum vulgare) to control powdery mildew (caused by E. graminis f.sp. hordei) was Mlg, introduced in Germany in the 1930s. Since then, successive waves of simply inherited resistances have been introduced in Europe as the pathogen overcame each in turn (Brown et al., 1997; Brown, 1995; Jorgensen, 1994; Wolfe and Schwarzbach, 1978; Wolfe, 1984; Wolfe et al., 1992; Wolfe and McDermott, 1994). The recent example of the Mlal3 resistance confirms the common process of an initial explosion of the newly selected virulence in one region followed by rapid and large-scale migration over a much larger area (Brown and Wolfe, 1990; Wolfe and McDermott, 1994; Wolfe et al., 1992). It is important to note that, although there is a tendency for European races of the pathogen to become more complex (accumulating more of the selected virulence genes in single genotypes), the European pathogen population remains highly diverse, even to the extent of different subpopulations on winter and spring barley (Caffier et al., 1996).

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However, massive changes in population structure may be due to migration alone. For example, Goodwin et al. (1995) found that the population of P. infestans in New York state was replaced within a year by migrants, presumably from Mexico. As a general principle, migration (gene flow of new virulence alleles) slows the loss of diversity in highly selected pathogen populations. Other examples are the apparent homogeneity of Stagonospora nodorum populations worldwide, which might be due to seed-borne migration (McDonald et al., 1994; Shah et al., 1995), and the rapid changes in cereal rust populations in Australasia due to new migrants (Burdon et al., 1982; Wellings and McIntosh, 1990). Where host-pathogen systems are left for long periods without selective interference by humans, two-sided coevolution between host and pathogen populations can occur. Evidence for such direct coevolution in an experimental agricultural ecosystem has been found in synthetic barley populations (composite crosses; CC) that were generated by intercrossing barley varieties from around the world (see Section III,B) (Harlan and Martini, 1929; Suneson et al., 1953) and that were then grown for more than 70 generations without conscious selection. From saved seed it was possible to track changes in gene frequencies over time, including resistance to Rhynchosporium secalis (causing scald). The interactions between host and pathogen populations were complex; the CC II and V populations, which were started at different times and from different sets of parents, did not evolve to the same level of resistance to common pathotypes of the scald pathogen, despite being grown in the same part of the field for many generations. However, it was possible to track changes in resistance gene frequencies over time that were consistent with selection and not genetic drift (Jackson et al., 1978; Muona et al., 1982; Saghai-Maroof et al., 1983; Webster et al., 1986). Levels of pathogenicity in "natural" R. secalis populations isolated from CC II and CC V corresponded to both the relative levels of resistance and the resistance genes in the host populations. Considerable genetic variation was maintained in both host and pathogen populations, presumably as a result of some form of frequency-dependent selection. The results were consistent with a dynamic coevolutionary process between R. secalis and the barley composite cross populations in which selection plays a prominent role (Allard, 1990; McDonald et al., 1989a,b; McDermott et aL, 1989). The CC populations also maintained diversity for resistance to barley powdery mildew although this disease rarely occurs in California. Population resistance to powdery mildew increased rapidly when one of the composite crosses was grown in a mildew-prone environment in the United Kingdom (Knight et al., 1988). Accumulation of resistances for barley mildew was also observed in a CC composed specifically for mildew resistance (CC XLII) (Reinhold et al., 1990).

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2. Host-Pathogen Coevolution in Nonagricultural Ecosystems In contrast to agroecosystems, there is usually a high degree of interspecific and intraspecific variability in other ecosystems. Also, the biotic and abiotic environments are more diverse, the spatial distribution of plants is usually more irregular, and natural evolutionary processes, such as selection, migration, and drift, are operating (Alexander, 1988; Anikster and Wahl, 1979; Browning, 1974; Harlan, 1976; Mundt and Browning, 1985). The differences between natural and agricultural ecosystems have consequences for the detection of coevolutionary interactions. Humans are often more sensitive than host plants to the effects of plant diseases and react by replacing whole and extensive populations of genotypes within short periods. For coevolutionary interactions to be discernible in nature, much longer timescales may be necessary. For example, over a period of 6 years, Manisterski (1987) found pronounced shifts in race composition of oat stem rust (caused by P. graminis f.sp. avenae) on wild oats (Avena sterilis) in Israel. However, these shifts could not be related to shifts in the resistance gene composition of the host population. The host effects might have been wiped out by the annual import of inoculum from Africa which has been documented (Dinoor, 1981). Natural host populations are generally much smaller than agricultural populations, and this, combined with the occurrence of unfavorable environmental conditions, may reduce the size of the pathogen population to the point where random genetic drift becomes a major force. For example, Burdon and Jarosz (1992) found evidence for frequent migration of the flax rust pathogen in Australia, probably due to the frequent occurrence of bush fires that eradicate the rust but not the host population, which can survive as seed. Frequent extinction and recolonization can lead to a geographically extensive adaptation of pathogens and hosts; for the wild flax-flax rust system, the scale extends to more than several h u n d r e d kilometers (Lawrence and Burdon, 1989). It has been claimed that disease levels in natural ecosystems are typically low (Antonovics and Levin, 1980; Borlaug, 1981; Burdon, 1978,1982; Burdon and Shattock, 1980; Dinoor and Eshed, 1984), though recent observations do not support this view (Burdon andJarosz, 1992;Jarosz and Burdon, 1991; Kranz, 1990). One of the reasons for these conflicting viewpoints is the variability of disease pressure on the host population among seasons and locations. The fitnesses of plant and pathogen may be determined independently by factors such as competition, microclimatic effects, spatial arrangements, and additional trophic levels. Genetic interactions between pathogen and host populations may thus be less pronounced and the correlation between the genetic composition of host and pathogen population may not be detectable at the time and spatial scales that are usually

7. Restriction of Plant Diseases Using Biodiversity

2]]

possible to study. Cyclical or chaotic behavior in population dynamics may be a further factor (May, 1976). Because of these difficulties, indirect measures are used to infer the occurrence of coevolution. For example, in environments conducive to oat crown rust (caused by Puccinia coronata), the genetic diversity for host resistance and for pathogen virulence was greater than in nonconducive environments (Burdon et al., 1983; Oates et al., 1983; Wahl, 1970). However, effects of the host on the pathogen population might be overridden by other environmental effects and additional fitness factors in the pathogen population. For example, in Israel an oat crown rust race possessing many different virulence genes allowing it to attack almost all host genotypes in the region (race 263) was still less fit than race 276, which possessed fewer virulences, because race 276 was able to reproduce and survive under a wider range of environmental conditions (e.g., Brodny et al., 1988). Similar observations were made by Katsuya and Green (1967) with wheat stem rust races. The array of possible interactive effects among hosts and pathogens in natural ecosystems is extremely complex. Coexistence of Silene alba and Ustilago violaceae, for example, may be possible only because the pioneer weed S. alba establishes in newly colonized areas before arrival of the pathogen, which can almost completely inhibit seed set (Alexander and Antonovics, 1988). Although it usually causes damage, disease might also give a selective advantage to a host, for example, by making the host unattractive to herbivores or by conveying greater disease a n d / o r drought resistance. For example, the grass Panicum agrostides when infected with Balansia henningsiana, an endophyte, produced heavier plants with more fillers than uninfected plants. Although many of these fillers were sterile, the absolute numbers of inflorescences were similar in infected and uninfected groups. Infected plants were also significantly less damaged by a leaf spot fungus (Alternaria solani) (Clay et al., 1989). With some endophytes, therefore, the line between pathogenesis and symbiosis cannot be clearly drawn (Clay, 1988, 1990). Pathogens can also affect host community composition (Augspurger, 1984; Zadoks, 1987), indicating the importance that higher levels of diversit),, especially species mixtures, could have in disease (and insect; see Section II,C,1) management in agriculture. In almost all studies involving nonagricultural host-pathogen systems, only the effects of pathogens on the genetics of the host but not vice versa have been considered (e.g., Alexander and Antonovics, 1988; Paul, 1990), leaving the question of the occurrence and especially of the timescale of coevolution partially unanswered. Clearly, nonagricultural ecosystems show us that, despite the evidence for host-pathogen coevolution in agricultural

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systems, its importance should not be overestimated. Factors such as plant competition, environmental effects, and herbivory may be as important or even more so than pathogens and act on a much shorter timescale as demonstrated, for example, by the work of Burdon and Jarosz (1992).

3. Interactions between Agricultural and Nonagricultural Ecosystems The separation of nonagricultural and agricultural ecosystems is not clear-cut because many plants may exist in both systems and pathogens do not respect the borders. For example, many rust pathogens spend part of their life cycle on agricultural and part on wild hosts indicating the close relationship between the two systems. The eradication of barberry (Berberis vulgare), the alternate host for P. graminis f. sp. tritici (the wheat stem rust pathogen) from the American Midwest (fields, forests, and house gardens) in the 1920s deprived the pathogen of the possibility of sexual recombination and overwintering in the north. This had far-reaching consequences for the epidemiology, resistance breeding, and gene deployment strategies (see Section IV). Incidentally, the barberry plants had served for fencing and the introduction of barbed wire allowed their removal. Similarly, wild and cultivated Ribes species act as alternate hosts for the uredial and telial stages of Cronartium ribicola (blister rust of Pinus cembra, P. strobus, and P. monticola). The introduction of P. strobus (Eastern white pine) from the United States, where blister rust was absent, into Eurasia in the early 18th century allowed for the rust to j u m p the species barrier from P. cembra to P. strobus in Siberia, which was then reexported to the United States in 1909 on infested seedlings causing huge epidemics in white pine stands in North America (Gaeumann, 1959). It is well known that susceptible pines cannot be grown near currant bushes in gardens in rust-conducive environments (M. Finckh, personal observation; Gaeumann, 1959). A similar example occurs with the alternation of the Gymnosporangium sabinae (pear rust) pathogen between pear and juniper in central Europe. Weedy wild barleys have also been shown to be of importance in the evolution of the Australian population of R. secalis (Burdon et al., 1994). Pathogen interactions among agricultural and other environments may be particularly common where crops are grown within or in close proximity to their centers of origin and diversity and where crop relatives occur in the n a t u r a l a n d weed flora. C. Exploiting the Coevolution of Host and Pathogen The understanding of the interactions between host and pathogen population genetics has led some workers to suggest alternative strategies for the use of resistance genes. The goals of such alternative strategies are as follows: 9 to achieve an acceptable level of disease;

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9 to achieve durable disease control; and 9 to control simultaneously all important diseases (and pests and possibly weeds), i.e., the development of a systems approach. Diversity can play an important role in the control of pests and pathogens (Wolfe, 1985; Wolfe and Finckh, 1997) provided such diversity is functional. Functional diversity is diversity that limits pathogen and pest expansion and that is designed to make use of knowledge about h o s t - p e s t / p a t h o g e n interactions to direct pathogen evolution (Mundt and Browning, 1985; Schmidt, 1978). The approaches to diversification can be at different taxonomic, geographic, and time levels. Such schemes span from simple cultivar mixtures to species mixtures, agroforestry, and permaculture systems.

1. Within-Field Host Diversification: Intraspecific Diversification During the past 30-40 years, management systems for diseases and insects based on intraspecific diversification have been studied and proposed that are practicable in mechanized agricultural systems. All that is required to gain from intraspecific diversity within a field is to mix desirable but disease-susceptible crop plant genotypes with genotypes that are resistant, or at least less susceptible. In the presence of disease, there will then be a strong tendency for the overall disease level to approach that of the more resistant component rather than that of the more susceptible component (e.g., Jeger et al., 1981; Wolfe et al., 1981 ). In addition, if the components show differential susceptibility to the pathogen in question, then further advantages in disease control may be obtained; this is the area in which most of the recent research has been directed. Intraspecific diversity in agricultural crops has been achieved through the use of near-isogenic line mixtures (NILs), multilines, or cultivar mixtures. NILs are produced by introducing different race-specific resistances into a recurrent parent (usually a commercial cultivar that has proven itself in commercial production) usually through five backcrosses that result in differentially resistant or susceptible lines of near-isogenic background (Jensen, 1988). Cultivar mixtures contain cultivars that are agronomically similar for traits such as harvest time and quality but diversified for properties such as resistance to various stresses. Multilines lie between NILs and cultivar mixtures in terms of the degree of genetic variation among the components and may be generated in different ways, e.g., by combining breeding lines from different backgrounds or by allowing for fewer backcrosses. Advantages and disadvantages of NILs, multilines, and cultivar mixtures have been summarized (Wolfe, 1985; Wolfe and Finckh, 1997). Several mechanisms may contribute to changes in disease incidence or severity (usually a reduction) in host populations that are diverse for resistance (e.g., Barrett, 1978; Browning and Frey, 1969; Burdon and Chilvers, 1982; Mundt and Browning, 1985; Van der Plank, 1968; Wolfe, 1985; Wolfe

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and Finckh, 1997). The first few of these apply to all systems, whether or not there is pathogen specialization to the host in question: (i) increased distance between plants of the most susceptible c o m p o n e n t in the mixture, (ii) further restriction of pathogen spread by resistant plants that act as barriers, (iii) selection in the host population for the more competitive a n d / o r more resistant genotypes can reduce (or sometimes increase) overall disease severity, and (iv) competitive interactions among host plants may affect plant susceptibility. Where pathogen specialization for host genotypes does occur, then, in addition, (v) pathogens nonvirulent on a host genotype may induce resistance reactions that work against virulent races, (vi) interactions a m o n g pathogen races (e.g., competition for available host tissue) may reduce disease severity, (vii) increased distance between host plants possessing the same resistance, and (viii) barrier effects are reciprocal, i.e., plants of one host genotype will act as a barrier for the pathogen specialized to a different genotype and plants of the latter will act as a barrier for the pathogen specialized to the first genotype. Because of the universality of these mechanisms with respect to airborne, splashborne, and some soilborne diseases, mixtures of host genotypes that vary in response to a wide range of plant diseases will tend to show an overall response to the range of diseases that is correlated with the disease levels of the components most resistant to each of the diseases. In addition, where particular components are affected by disease, there is a tendency for less affected components to compensate for them in terms of yield. Substantial reductions of several foliar diseases have been reported in experiments with multilines and cultivar mixtures of cereals (Alexander et al., 1986; Chin and Ajimilah, 1982; Bonman et al., 1986; Finckh and Mundt, 1992a,b; Koizumi and Kato, 1987; McDonald et al., 1989b; Wolfe, 1987; Wolfe and Barrett, 1980). Cultivar mixtures and multilines are being used on a commercial scale in the United States (wheat, oats), Denmark, Germany, Poland, Scotland, and Switzerland (barley), and Colombia (coffee) to control, respectively, wheat yellow rust, oat crown rust, barley mildew, and coffee rust (Wolfe and Finckh, 1996). When used on more than 300,000 ha in the former German Democratic Republic, powdery mildew of barley was reduced by 80% in barley cultivar mixtures within 5 years (Wolfe, 1992). A potentially important aspect of disease restriction in diversified host populations could also be threshold density, which plays an important role in animal populations. Below a certain host density, infectious diseases do not spread: Factors such as hygiene are important here. This is analogous to plant diseases, where sanitation is especially useful when plant density is relatively low. However, if there are many host plants concentrated together, both within and among fields, the potential for inoculum production is

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large so that plants even in a well-managed field are likely to become diseased. If the host density is low, inoculum pressure might be so low that good m a n a g e m e n t for microclimatic conditions, nutrient status, and other sanitation measures may suffice to prevent or delay epidemics. Beyond the inherent durability of the components of the host population, durability of resistance in diversified systems depends primarily on the ability of the pathogen to evolve so-called "super races," i.e., genotypes able to attack all resistance genes in the host population (Mundt, 1994), although we know of no such occurrences. This question has led to much theoretical modeling and debate together with some small-scale field experiments and data collection from areas where mixtures were used on a large scalemin former East Germany and Poland (Mundt, 1994; Wolfe and Finckh, 1997). Wolfe and Finckh concluded: The indications from the small-scale field experiments, models and other data, are that complex races can be selected more or less quickly leading to a reduction in effectiveness of mixtures, though this is likely to be slower than the dramatic "breakdowns" that are c o m m o n in monoculture. [However,] The rates of change that do occur suggest that there should be time to allow for planned changes in the composition of host mixtures (p. 386).

Intraspecific diversification also offers possibilities for insect pest control. For example, van E m d e n (1966) drew attention to possibly beneficial effects of greater intravarietal diversity in the oat-frit fly (Oscinella frit L.) system. The flies attack the host plants only at a particular growth stage and phenological variation within an oat crop could allow for escape from attack and for subsequent compensation in growth. Varietal mixtures have been tested for the control of various insects on diverse crops; results from such experiments were generally encouraging though variable with reductions in pest attacks in some cases and increases in others (see Andow, 1991, for a comprehensive review). The mechanisms altering insect attacks in diverse systems are more complex than for the p a t h o g e n - p l a n t interactions because, in addition to the host plant and the insect pest, predators and parasites of the insects have to be considered. As with pathogens, modes of dispersal, reproduction, and recombination are highly variable among insects. Differences in ability to disperse and to select a landing place will greatly influence the relative importance of any specific mechanism (Andow, 1991). The use of resistant hosts might lead to the concentration of insects on susceptible hosts of the same species (in adjacent fields or plants) or of alternate host species (Kennedy et al., 1987). Such potential side effects have to be considered carefully and benefits and costs need to be balanced within the agroecosystem and not just within a given crop. Because of the generally less p r o n o u n c e d effects of varietal mixtures on insects, intrafield diversification for the m a n a g e m e n t of insect pests has focused more on the use ofpolycultures or intercropping (e.g., Bach, 1980;

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for reviews see Andow, 1991; Altieri, 1994; Altieri and Letourneau, 1982; Risch et al., 1983). Smithson and Lenne (1996) point out the large amount of research but relatively little use of intraspecific diversification in the developed world, in contrast to the little research and very extensive use in the developing world. They concluded that the overall advantages of the approach demand development of appropriate research, particularly for sustainable, subsistence agriculture.

2. W~thin-Field Host Diversification: Interspecific Diversification

Species mixtures have a greater potential in diversifying resistance because each component used may often be a nonhost for most if not all the pathogens that can infect the other components. This means that the level of restriction may be high for each disease and there is no response to selection for races of pathogens able to attack more than one component. However, there are some cases in which pathogens infect more than one species, particularly among soilborne pathogens. Among airborne pathogens, an example is the stem rust pathogen that attacks both barley and wheat in North America (Liu et al., 1996). In this case, susceptible barley and wheat cultivars will represent a monoculture with respect to resistance to stem rust The combinations and permutations for species mixtures are almost endless and at different systems levels, including incorporation of cultivar mixtures. Some species mixtures have been widely used for many years, for example, in temperate and tropical, short-term and long-term pastures. Cereal species mixtures for feed production are currently grown on more than 1.4 • 1 0 6 ha in Poland and have been shown consistently to restrict diseases (Czembor and Gacek, 1996). Recent experiments in Poland also demonstrate possible effects on weeds in cereal and cereal-legume species mixtures (E. Gacek, personal communication; see also Bulson et al., 1990). In Switzerland, the "maize-ley" system (i.e., maize planted without tillage into established leys), which is being promoted to reduce soil losses and nutrient leaching, has been shown to reduce smut (caused by Ustilago maydis) and attack by European stem borer (Ostrinia nubilalis) and aphids (Bigler et al., 1995). A newly developed low-input system for growing wheat with a permanent understory of white clover (Trifolium repens) greatly reduces the major pest aphid species and slugs (Jones and Clements, 1993). In addition, we speculate that there should also be substantial reductions in splash-dispersed diseases, such as those caused by Septoria spp. Some of the most intensive and diversified mixed-species cropping is practiced in China. Harwood and Plucknett (1981) described a multitude of different intercropping systems and remarked that diseases and insect pests were, if at all, of only minor importance. Systematic experimental research on optimizing intercropping is being carried out in China.

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The gardening literature refers to numerous examples of companion planting for the limitation or prevention of a wide range of pests and pathogens; some of these appear to be generally effective and others much less so. Authors usually point out that companion planting is site specific, also, the effects may be quite specific and time dependent. Thus, although Riotte (1983) claims that marigolds (Tagetes patula) repell certain nematodes and thus also protect its neighbors, French (1994) warns that marigolds will push the nematodes toward their neighbors when planted together, they are beneficial only if planted before the susceptible plants. In addition to effects on pathogens, pests, and weeds, inter- and intraspecific diversification may play an important role in buffeting crops against unpredictable abiotic stresses (e.g., weather and weather-induced factors). This may be part of the reason for the often poor correlation between the disease levels in crop mixtures and the effects of those diseases on crop yields.

3. Systems Diversification: Agroforestvy and Permaeulture The forms of diversification described previously refer mainly to the within-field level. The next higher level of diversification is at the whole farm or the agricultural system. There are now many examples of agroforestry systems (intercropping trees and field crops or silvopastural production systems) in the tropics (e.g., Dwivedi, 1992; Singh et al., 1994), but there is also a considerable potential for integrating tree production in temperate agriculture through farm forestry (trees separated from field crops), agroforestry, or, indeed, "woody agriculture," where food, energy, and raw materials are produced by the tree crop (Rutter, 1989). One of the most holistic approaches to diversified agriculture is encompassed in the concept ofpermaculture (Mollison, 1990). Permaculture (from permanent agriculture) encompasses the whole living environment, which is carefully designed to produce as much as possible food, raw materials, and energy that are locally required with a minimum of external inputs; this now includes social and economic interactions as part of the concept (Whitefield, 1993). In such diversified, sustainable agricultural systems, the nature of pest and disease management may no longer be well defined because the most important strategy is avoidance of problems through system design (Bird et al., 1990). Many disease control methods in traditional systems are indeed no more than strategic design (Thurston, 1992). For example, density of maize (Zea mays) plantings in Indonesia is adjusted by farmers to provide enough ventilation to reduce infection by downy mildew (caused by Peronosclerospora maydis) (Thurston, 1992). Planting depth and timing, together with site selection, are other strategic decisions often made by growers.

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III. The Breeder A. Conventional Breeding Approaches to Durable Resistance: Inherent Durability The identification of durable resistance is a large-scale process; such resistance can only be identified post hoc and it cannot be predicted in a breeding program. The only possibility to increase the probability of obtaining durably resistant progeny is to use durably resistant parents. This may limit progress in other directions in the breeding program. Flor (1956) proposed the use of resistance gene combinations or pyramids in hosts to decrease the probability of a new pathogen race occurring. The probability hypothesis relies on a lack or very low rate of recombination in the pathogen population and pyramids have therefore only a limited scope of application. Also, the greater durability that has been observed with some resistance gene combinations may be a function of the particular genes used and not of reduced probabilities (Mundt, 1990). The most sophisticated approach to the breeding of resistance gene pyramids has been taken by rice (Oryza sativa) pathologists and breeders who are applying detailed knowledge of the blast pathogens' (Pyricularia grisea) population structure and the fact that certain resistance genes appear to provide resistance to whole pathogen lineages (Zeigler et al., 1994, 1995). This approach relies on a lack of migration and sexual and other forms of recombination among fungal lineages. Recent findings suggest, however, that parasexual recombination may be common in this pathogen (Zeigler et al., 1997). Also, in some of the centers of diversity of rice blast, the pathogen population is in gametic equilibrium (i.e., all tested genetic markers are randomly associated, indicating that random recombination is taking place) with no evidence of lineage subdivision. Monogenic resistances have been durable (e.g., Van Ginkel and Rajaram, 1993) and race nonspecific in some cases (Parlevliet, 1993) but are considered more likely to be overcome than oligo- or polygenically inherited resistances. Breeding for partial resistance of barley to a n u m b e r of diseases has also been successful (Parlevliet, 1989). However, race-non-specific a n d / or partial resistance is not always available a n d / o r is difficult to identify and incorporate into a crop (Johnson, 1984; Leonard and Mundt, 1984; Parlevliet, 1989; Van der Plank, 1968). Another difficulty is that resistances reported earlier to be race nonspecific have later been shown to be race specific (see Parlevliet, 1989, for examples). A selection scheme for partial resistance in oats to crown rust has been in place since 1953 in Minnesota, where the rust's sexual host (Rhamnus cathartica) is grown in close proximity to the test plots of differentials, cultivars, and breeding lines to facilitate recombination in the pathogen

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(Moore, 1966). Some durably resistant oat lines have resulted from this approach despite difficulties in selection due to induced resistance and other confounding factors (K. Leonard, personal communication). Some progress has been made in the analysis of traits contributing to durable resistance. For example, recombinant inbred lines of the rice cultivar Moroberekan were analyzed with RFLPs to identify markers linked to resistance. A large number of quantitative trait loci (QTLs) were identified in addition to a few major resistance genes. The identified markers allow the pyramiding of QTLs together with major genes into cultivars through marker-assisted selection (Wang et al., 1994).

B. Improving Intraspecific Diversity There is a considerable literature on the analysis of genotypes for their mixing ability (e.g., Allard, 1960; Baker and Briggs, 1984; Federer et al., 1982; Gacek et al., 1996; Knott and Mundt, 1990). One important result is that high-yielding cultivars bred for production in pure stands are often effective in mixtures despite earlier contrary predictions (e.g., Hamblin and Donald, 1974). However, mixing ability analyses require experimentation with pure stands and mixtures and conclusions about the mixing ability of a set of cultivars cannot be extended to cultivars that have not been tested. Instead of expensive experimentation, breeding of mixtures for high performance, for example, via bulk selection, in composite crosses or by top crosses (see below) could reduce costs and increase genetic diversity without sacrificing other advantages of modern high-yielding varieties and at the same time improve ecological combining ability (see below). For a composite cross, diverse varieties or lines are intercrossed in all combinations. The F1 plants are then grown as a bulked hybrid population for subsequent generations without conscious selection. This has been termed an "evolutionary plant breeding method" (Harlan and Martini, 1929; Jensen, 1988; Suneson, 1956). Allard and Adams (1969) found that genotypes from such a composite cross of barley that had not been exposed to conscious selection by humans over 18 generations showed significantly higher positive yield synergisms when grown in mixtures than did a mixture of cultivars that had not coevolved. A parallel analysis of the effect of neighboring genotypes on each other led the authors to the conclusion that, in the composite cross, there had been selection both for good competitors, i.e., a genotype yields more when bordered by another genotype than by itself, and for good neighbors, i.e., a genotype induces a mean increase in yield when bordering another genotype. The "ecological combining ability" to which Allard and Adams refer is the combination of good competitive ability and neighborhood effects. In addition to greater ease of selecting for ecological combining ability, composite crosses can play an important role in genetic resource conservation (Allard, 1990).

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Kilen and Keeling (1990) tested whether labor-saving bulk selection in the field could be used to improve host population resistance. They exposed a bulked soybean (Glycine max) population produced through a single cross with known initial frequencies of the genes Rpsl-b and Rps3, conferring resistance to races 1 and 3 of Phytophthora rot (caused by Phytophthora megasperma), respectively, for 5 years to race 1 of the pathogen in the field. They found that the Rpsl-b gene increased significantly in frequency, whereas the Rps3 gene did not. In pearl millet (Pennisetum glaucum) Mahalakshmi et al. (1992) used groups of selected landraces as pollinators for high-yielding lines (i.e., top crossing). From the progeny, they were able to greatly increase yield responsiveness to improved environmental conditions, compared with the landraces, while at the same time maintaining the high yield stability of the original landraces. The authors found that not only did the top cross hybrids always outyield their pollinators but also yield increases were greater for the low-yielding landraces. They concluded that "if this is generally the case, breeding efforts could thus be concentrated on adaptive traits such as disease and insect resistance, and their combining ability and fertility restoration in the breeding of topcross pollinators rather than on yield potential" (p. 932). Maintenance of locally adapted genetic diversity might also be facilitated by promoting only partial replacement of farmer's seeds mixtures with improved varieties. For example, Trutmann and Pyndji (1994), in Zaire, replaced various proportions of local bean varieties with high-yielding lines resistant to angular leaf spot (caused by Colletotrichum lindemuthianum). At replacement rates of 25-50%, disease on the local varieties was greatly reduced and yields of both the local and the high-yielding mixture components were increased between 16 and 24%. Thus, although the susceptible varieties benefited greatly from the epidemiological effects, the resistant lines also benefited from the plant-plant interactions. Because seed is selected with great care by farmers to maintain variability of traits in subsistence agricultural systems (Sperling et al., 1993), there is reason to expect that amendment of seed sources with new high-yielding resistant material and then leaving the mixtures to farmers' selection should protect them from undue loss of genetic diversity. In summary, intraspecific diversity could be improved both by directed selection for mixture performance and by using novel approaches to the generation of diversity.

C. Interspecific Mixing and Selection Farmers grow species mixtures in many parts of the world even though, with the exception of pastures, almost no breeding effort has been invested in such systems. For example, in Poland, despite earlier official discourage-

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ment, the area grown with cereal species mixtures increased steadily over the past 30 years. Farmers tended to maintain older varieties for this purpose that were known to perform well in mixtures (Czembor and Gacek, 1996). Formal efforts by public breeders to improve species mixtures have now started (Daellenbach et al., 1996; E. Gacek, personal communication). Selection for interspecific mixing ability is a complex issue and there is no general concept on how this should be done. Wright (1983, 1985) developed statistical methods for the selection of components for interspecific or intergenotypic mixtures and discussed long-term effects of different selection methods. The greatest problem with any mixture trial is the exponential increase of treatments required when many possible combinations are to be tested. There has been little research on the genetic a n d / o r physiological factors necessary for a good mixing partner. Common sense suggests that genotypes that complement each other in root and shoot architecture may compete least for below- and aboveground resources. However, competitive abilities of plants are always measured relative to others and there is still no measure for the absolute competitive ability of individual plants, thus making predictions exceedingly difficult. It would be of great interest to determine if physiological measures, such as the water and nutrient extraction potential of plants, could be used to predict their competitive ability when grown together. There is only scant literature on breeding for multiple cropping and mixtures (see reviews by Francis, 1990; Jensen, 1988; Smith and Francis, 1986). The most important resource for breeders in breeding for mixtures may be farmers who have long-standing experience in growing mixtures. This was demonstrated by Sperling et al. (1993), who found that the success of heterogeneous bean varieties in Rwanda was greater when selected by local farmers than when selected by breeders. It is the interaction of farmers and breeders that produces the best results. D. Breeder Protection

Varietal and species mixtures may consist of seed produced by different breeders leading to possible difficulties in the distribution of royalties, particularly if one or two generations of seed increase are necessary before mixtures are sold. Inevitably, the component frequencies in such seed mixtures will differ from the original frequencies, which poses legal difficulties because accurate labeling is not possible. Breeders to whom we have spoken feel that sharing of royalties proportionally to the initial mixture frequencies should be acceptable; there should also be the advantage of durable seed sales. To help avoid the problem of limiting mixture diversity to the products of a single company, it would be preferable to separate the breeding and marketing of seeds.

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Registration of diversified varieties currently presents legal difficulties both in Europe and in the United States because of the Union for the Protection of New Varieties (UPOV) guidelines in Europe and the Plant Varietal Protection Act (PVPA) in the United States, which require that a variety must be uniform genetically and in appearance and be readily distinguishable from other varieties in order to be accepted for registration. This ensures that newly registered varieties are not old varieties renamed and provides protection for a genuinely novel product. However, varieties registered after the PVPA came into effect often differed only in agronomically minor and unimportant traits that could be used for differentiation and description (Kloppenburg, 1988). Moreover, there are serious biological constraints associated with the requirement for homogeneity. Innumerable varieties and landraces have disappeared from the market because they did not fulfill the laws' requirements. For example, it has been estimated that approximately 75% of all vegetable varieties in Europe have disappeared within 10 years since the inception of UPOV in 1961 (Mooney, 1979). Indeed, great concern has been voiced worldwide about the precipitous genetic erosion in agriculture due to legislative measures, general breeding methods, and genetic engineering technology (e.g., Fowler and Mooney, 1990; Kloppenburg, 1988). The first legislative attempt to allow for the legal maintenance and sale of genetically diverse and nonhomogeneous cereal landraces and so-called "population varieties" was initiated in Switzerland through the "Ordinance on Production and Circulation of Cereal Seed" (Verordnung ~ber die Produktion und das Inverkehrbringen von Getreidesaatgut) from December 23, 1994, by the Department of National Economy. Varieties are here defined as: "a totality of plants within the lowest level of a botanical taxon independent of the criteria that need to be fulfilled for varietal protection" (translated by the authors). Under that definition, the criteria of distinguishability, homogeneity, and constancy that are necessary for breeders' rights are uncoupled from the definition of a variety (Articles 4 and 5). It is then allowed explicitly to sell and circulate nonhomogeneous materials in order to maintain the biodiversity of a species. Specific rules as to the labeling and amount of trade allowed apply and only Swiss landraces can be grown in Switzerland (Article 22). The ordinance also provides for the registration of breeding lines for the sole purpose of being used in line mixtures for disease and other stress control. Such breeding lines are subject to the same protection rules as varieties. Although the ordinance points in the right direction, there is still no provision for the release of diversified varieties, such as composite crosses or top crosses, because they do not comply with UPOV rules. It is understandable that breeders, especially in the private sector, must be rewarded for their work and one way is through royalties. However, in

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the current situation, the PVPA and the UPOV convention prevent the inclusion of genetic diversity for disease, pest, and other abiofic stress resistances into population varieties. There is a need to find new solutions that will allow breeders to be compensated for their efforts without constraining the potential for improving yield stability and the durability of disease and pest resistance in practical agriculture through intracrop diversity.

IV. The Farmer Farmers who want to be successful need to be good agriculturists, economists, and ecologists. They are confronted constantly with economical and ethical/philosophical problems requiring decisions that often are, or appear to be, mutually exclusive in their consequences. Ecological and economical concerns can lead to the same conclusion, however. For example, during the 1980s, the East German government imposed a change in spring barley management from production in large fields of single varieties to cultivar mixtures to preserve the varieties' resistance and to save on fungicide use that had become necessary to prevent major losses from powdery mildew. Fungicide needs for mildew control decreased by as much as 80% without loss of yield and with consequent large savings over a 6-year period (Wolfe, 1992). Polish farmers have been growing cereal species mixtures on an increasing scale over the past 30 years because the mixtures greatly reduced risk (Czembor and Gacek, 1996). It is also to minimize risk that subsistence farmers in many parts of the world rely on some form of mixed cropping and often they deliberately select mixtures (Bonman et al., 1986; Smithson and Lenne, 1996; Sperling et al., 1993). If it is economically attractive for farmers to produce within a diversified system, they will choose that option (M. Wolfe, unpublished data). Farmers, however, are dependent on land distribution patterns, consumer preferences, the economic system, plant variety legislation, political decisions, and society at large because it influences agriculture and food policies.

V. The Agronomist/Adviser Agricultural advisers need to consider diversification strategies for disease control not only at the farm level but also at the interfarm level. This includes the development of strategies for the constant rotation of mixture composition over time to delay pathogen adaptation (gene deployment in time), diversification on regional or continental scales (regional gene

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deployment), and the integration of different available management methods. Often a conflict of interest among farming methods has to be dealt with. For example, no or reduced tillage, which is an integral part of integrated farming practices (IFP), may reduce erosion but at the same time increase certain disease problems. However, many of these problems can be taken care of by appropriate crop rotations and green manure treatments that are also part of IFP (e.g., Davis et al., 1996; Teich, 1994). For example, mulches and minimum tillage are known to increase earthworm populations and these have been shown to positively affect Rhizoctonia bare patch (caused by Rhizoctonia solani) and take-all (caused by Gaeumannomyces graminis) of wheat, two diseases for which no genetic resistance is available (Stephens et al., 1994 a,b,c). In cereal production in Germany, Odoerfer et al. (1994) showed that the use of pesticides alone was not sufficient to achieve maximum yield. This was only possible when rotations were used, indicating that factors in addition to disease play a crucial role in determining yield. Deployment in time of resistance to the green leaf hopper (Nephotettix virescens), the vector of Tungro disease of rice, in combination with synchronous planting has been shown to contribute to the control of the disease in the province of South Sulawesi in Indonesia. Rice varieties with different green leafhopper resistance genes are rotated between seasons to prevent the buildup of hopper populations highly virulent on any one variety (Manwan and Sama, 1985; Sama et al., 1991). There is a possibility for "recycling" defeated resistance genes after the previously selected virulent pathogen or insect strains have decreased in frequency (Wolfe, 1992). However, this will work only if, in the absence of selective host resistance, there is selection against the corresponding virulence, leading to a drastic decrease in its frequency. This approach has been successful for the control of Hessian fly (Mayeticola destructor) on wheat (Gallun, 1977; Hare, 1994). For regional gene deployment, host genotypes diverse for their resistances are planted in different fields or geographic areas. This is most useful against pathogens that are dispersed from areas where they overwinter or oversummer to areas where they usually cannot persist and the epidemic is dependent on the introduction of outside inoculum, e.g., by wind (Browning et al., 1969; Van der Plank, 1968). If the resistances in the host populations differ among the regions, then a pathogen race on its way along its usual seasonal pathway will be effectively stopped when encountering only resistant hosts in an area. However, if inoculum virulent on the hosts grown in that region can persist in that region, i.e., the pathogen is residual, then the strategy will fail (Van der Plank, 1963). Regional gene deployment strategies have been proposed for potato late blight (Van der Plank, 1963), for breaking the "Puccinia path" of oat

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crown rust (Browning et al., 1969) and wheat stem rust (Knott, 1972; Van der Plank, 1968) in central North America, and to control barley powdery mildew and wheat stripe rust in the United Kingdom and Europe in general (Priestley and Bayles, 1982; Wolfe and Barrett, 1977, Wolfe, 1992). None of these have been or are likely to be directly successful because other priorities of farmers and breeders are deemed more important.

Vl. The Consumer A. Product Quality

Concerns over product quality are said to originate from the consumer but they are often led by the industry. For example, a longer shelf-life is arguably of greater benefit to the supermarket than to the individual consumer. It has also been questioned if consumers really are so concerned about every last blemish on fruit and vegetables or if they are conditioned to be this way (Clunies-Ross and Hildyard, 1992). It appears that consumers, and farmers, are often led to believe that field mixtures would reduce the product quality but without real evidence. Indeed, maltsters usually mix different varieties together for malting to achieve a desired malting quality and recent data have shown that the malting quality of a batch of barley is d e p e n d e n t much more on the conditions u n d e r which it was grown than on the individual variety. Furthermore, variety mixtures of the same quality class can provide a more stable quality across environments than the single c o m p o n e n t varieties (Baumer and Wybranietz, 1995). The case is similar for wheat processing, in which millers mix together different batches of grain that were all tested separately, according to the quality requirements of processors. This could also be achieved with batches of cultivar mixtures. Although, in general, it is difficult to market mixtures in Europe, no such difficulty has been found in the Pacific Northwest of the United States (C. Mundt, personal communication). Indeed, a local cooperative of IFP farmers in southern Germany who are producing on the basis of cultivar mixtures are sometimes unable to provide sufficient grain for the demands of millers and bakers (El Titi, personal communication). Coffee is often regarded as being a particularly sensitive crop from the point of view of quality. However, beans of uniform high quality are produced in Colombia from mixtures that have been selected to be variable in terms of rust resistance but uniform for quality characteristics (Browning, 1997; Moreno-Ruiz and Castillo-Zapata, 1990); such mixtures are now produced on some 350,000 ha.

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Mixtures of cereals and legumes, for example, wheat and beans, can be used directly for animal feed; planting the mixture requires much less energy than mixing the components after harvest. Any necessary adjustment to the composition can be easily checked and made.

B. Technical Aspects A common argument against crop diversification is that such practices are inappropriate for mechanised cultivation. However, there are many simple technological changes that could make mixed cropping more attractive. For example, it would not be difficult to divide the hopper of a cereal seed drill into sections to be filled with different varieties, thus avoiding the need for premixing seed. For harvesting, modern technology for mechanical or electronic separation of seeds can be easily exploited, particularly where there are large differences among the component seeds, for example, between cereals and legumes. Electronic sorting could also be applied to the separation of different fruit varieties. In vegetable production, mixed cropping might be generally more feasible because the manual labor input is very high to start with. Besides possible positive effects on disease, strip cropping is also used as an effective tool in crop management. Vegetables, field crops, and fruit trees are planted on high beds to enhance drainage during the wet season in China, Taiwan, Thailand, Indonesia, and the Philippines (Sorjan farming system, Hoque, 1984). In some of these Southeast Asian countries drainage ditches are used to grow additional crops of rice, water hyacinth, and edible snails (Luo and Lin, 1991), a system that has been adapted for experimental research at the Asian Vegetable Research and Development Center in Taiwan (C. Th6nnissen, personal communication). Strips of cultivars rather than intimate mixtures may help reduce unwanted intergenotypic competitive effects while still providing adequate disease control (e.g., Brophy and Mundt, 1991; Huang et al., 1994). Technical constraints may often be more a problem of perception than of reality. For example, production of seed mixtures does not appear to pose an insurmountable problem to seed suppliers in the Pacific Northwest of the United States. There, variety mixtures are in great demand by wheat growers who now grow more than 100,000 ha of mixtures (C. Mundt, personal communication). In vegetable production, which is much more labor-intensive, diversified production (e.g., strip planting) is commonly practiced. Reasons for this include the need to continuously supply the markets with fresh produce and to reduce risks from crop losses. Interestingly, in the past few years, the extension of diversity among salad leaf crops, encouraged by the consumer, has enabled the grower to spread his/her risk among a wider range of species, thus reducing dependence on lettuce (Lactuca sativa) and

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the associated problem of lettuce downy mildew (Bremia lactucae), which is expensive and difficult to deal with because of the genetic variation in the pathogen allowing it to overcome resistant varieties and fungicides in intensive production.

VII. Politicians and Economists Short-term market considerations and positioning are often the most important criteria for political and economical actions rather than the long-term sustainability of systems. In addition, the global economic framework, such as the General Agreement on Trade and Tariffs and public debts, often places limits on locally and especially on environmentally useful actions. Government policies have been and must continue to be concerned with food production to meet the demands of the burgeoning world population. However, we now recognize that policies concerned solelywith production are not sustainable, leading, in particular, to loss of soil by mismanagement, which is compounded by other policies leading to extension of urbanization. A large contributory aspect is dependence on monoculture (particularly at the level of variety or resistance) with consequent loss of biodiversity, which requires massive support from external inputs, particularly pesticides. It is often claimed that even higher inputs will be required to produce the food necessary to meet future demands. Clearly, some inputs will always be needed for food production in comparison to a natural ecosystem. The question is, what is agronomically, ecologically, ethically, and economically viable and acceptable? For example, there is growing evidence that the increase in production is often much smaller than expected, based on inputs such as fertilizers (Brown and Kane, 1994; Cassman et al., 1995; Diwan and Kallianpur, 1985). In our view, changes in policy toward improved methods of production, of the kind already instituted in countries such as Switzerland and Austria, can help to change the balance, rewarding strategies that lead to increased exploitation of biodiversity while effectively punishing those strategies that lead to nonsustainable exploitation of soil and monoculture. With sufficient backing from appropriate research and development (which also requires considerable changes in policy), such policies will, in the long term, through their impact on greater sustainability of production be less expensive for governments by providing the same or greater production at less cost. In this sense, crop diversification can deliver many benefits in terms of soil maintenance and enhancement; disease, pest, and weed control; and more efficient employment of labor through, for example, reduced seasonality. We already discussed in section III,D some of the implications of the current system of breeder protection for agricultural production based

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on diversification. The juxtaposition of breeders' rights and interests versus the current and future needs of society at large is a serious dilemma. Plant breeders are rendering a service to society and deserve to be recognized and compensated for this service. However, the compensation must not compromise the genetic diversity and thus the future ability of our crops to defend themselves from biotic and abiotic stresses (see also Clunies-Ross, 1995). It may therefore be necessary to separate plant breeding from other agribusiness undertakings such as seed and agrochemical production.

VIII. Society at Large and Future Perspectives Whereas agricultural production has risen steadily and at times explosively between 1950 and 1990, we cannot expect it to continue to rise at the same rate. This is because agricultural land is being lost at an everincreasing rate due to environmental degradation, industrialization, and settlement in a world with a yet unchecked population growth (Brown and Kane, 1994). Stable agricultural systems together with a massive increase in tree planting, which reduce or eliminate erosion, salination, and other factors leading to the loss of productive land, need to be developed in order to ensure the necessary food security for h u m a n society to be stable (Brown and Kane, 1994; Mollison, 1990). An important contribution already comes from exploitation of biodiversity in cropping systems in the developing world. We believe, with Smithson and Lenne (1996), that this should be developed much further in the developed world. To place this in a broader view, we know that ecological interactions are highly dynamic and subject to change, but that changes occur at an evolutionary timescale, which is usually far longer than the relevant h u m a n timescale of planning and operation. Normally, therefore, we have to take ecological interactions as given parameters that we can only try to learn about and to make use of to improve agricultural systems. We cannot change the basic interactions in our timescale. H u m a n society is also based on interactions, but changes in our perceptions of how systems need to change can be much faster than adaptation in ecosystems. Thus, although we can learn about ecology and make use of what is there, we can also learn about h u m a n society so as to be able to change and modify important factors in agriculture. In this sense, we have tried to point out that we should not allow our attitudes and laws to constrain us from rational and novel exploitation of biodiversity in our agricultural ecosystems.

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Acknowledgment We thank J. A. Browning for providing helpful comments on the manuscript.

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Teich, A. H. (1994). Disease control in wheat using ecological principles. Genet. Pol. 35B, 127-135. Thompson, J. N. (1982). Evolutionary ecology, interaction, and coevolution. In "Interaction and Coevolution" (J. N. Thompson, ed.). Wiley, New York. Thurston, H. D. (1992). "Sustainable Practices for Plant Disease Management in Traditional Farming Systems." Westview, Boulder, CO. Tilman, D., Wedin, D., and Knos, J. (1996). Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379, 718-720. Trutmann, P., and Pyndji, M. M. (1994). Partial replacement of local common bean mixtures by high yielding angular leaf spot resistant varieties to conserve local genetic diversity while increasing yield. Ann. AppL Biol. 125, 45-52. Ullstrup, A.J. (1972). The impacts of the Southern com leaf blight epidemics of 1970-1971. Annu. Rev. Phytopathol. 10, 37-50. Van der Plank, J. E. (1963). "Plant Diseases: Epidemics and Control." Academic Press, New York. Van der Plank, J. E. (1968). "Disease Resistance in Plants." Academic Press, New York. van Emden, H. F. (1966). Plant insect relationships and pest control. World Rev. Pest Control 5, 115-123. Van Ginkel, M., and Rajaram, S. (1993). Breeding for durable resistance to diseases in wheat: An international perspective. In "Durability of Disease Resistance" (T. Jacobs and J. E. Parlevliet, eds.), pp. 259-272. Kluwer, Dordrecht. Wahl, I. (1970). Prevalence and geographic distribution of resistance to crown rust in Avena sterilis. Phytopathology 60, 746-749. Wang, G. L., Mackill, D.J., Bonman, J. M., McCouch, S. R., Champoux, M. C., and Nelson, R.J. (1994). RFLP mapping of genes conferring complete and partial resistance to blast in a durably resistant rice cultivar. Genetics 136, 1421-1434. Webster, R. K., Saghai-Maroof, M. A., and Allard, R. W. (1986). Evolutionary response of Barley Composite Cross II to Rhynchosporium secalis analyzed by pathogenic complexity and by gene-by-race relationships. Phytopathology 76, 661-668. Wellings, C. R., and McIntosh, R. A. (1990). Puccinia striiformis f. sp. tritici in Australasia: Pathogenic changes during the first 10 years. Plant Pathol. 39, 316-325. Whitefield, P. (1993). "Permaculture in a Nutshell." Permanent, Clanfield Hampshire, UK. Wolfe, M. S. (1973). Changes and diversity in populations of fungal pathogens. Ann. Appl. Biol. 75, 132-136. Wolfe, M. S. (1984). Trying to understand and control powdery mildew. Plant Pathol. 33, 451-466. Wolfe, M. S. (1985). The current status and prospects of multiline cultivars and variety mixtures for disease resistance. Annu. Rev. Phytopathol. 23, 251-273. Wolfe, M. S. (1987). The use of variety mixtures to control diseases and stabilize yield. In "Breeding Strategies for Resistance to the Rusts of Wheat," pp.91-99. CIMMYT, Mexico D.F. Wolfe, M. S. (1992). Barley diseases: Maintaining the value of our varieties. In "Barley Genetics VI" (L. Munk, ed.), pp. 1055-1067. Munksgaard, Copenhagen. Wolfe, M. S., and Barrett, J. A. (1977). Population genetics of powdery mildew epidemics. Ann. N.E Acad. Sci. 287, 151-163. Wolfe, M. S., and Barrett, J. A. (1980). Can we lead the pathogen astray? Plant Dis. 64, 148-155. Wolfe, M. S., and Finckh, M. R. (1997). Diversity of host resistance within the crop: Effects on host, pathogen and disease. In "Plant Resistance to Fungal Diseases" (H. Hartleb, R. Heitefuss, and H. H. Hoppe, eds.), pp. 378-400. Fischer-Verlag, Stuttgart. Wolfe, M. S., and McDermott, J. M. (1994). Population genetics of plant pathogen interactions: The example of the Erysiphe graminis-Hordeum vulgare pathosystem. Annu. Rev. Phytopathol. 32, 89-113.

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Wolfe, M. S., and Schwarzbach, E. (1978). Patterns of race changes in powdery mildews. Annu. Rev. Phytopathol. 16, 159-180. Wolfe, M. S., Barrett, J. A., and Jenkins, J. E. E. (1981). The use of mixtures for disease control. In "Stategies for the Control of Cereal Diseases" (J. F. Jenkyn and R. T. Plumb, eds.), pp.73-80. Blackwell, Oxford. Wolfe, M. S., Braendle, U. E., Koller, B., Limpert, E., McDermott, J. M., Mueller, K., and Schaffner, D. (1992). Barley mildew in Europe: Population biology and host resistance. Euphytica 63, 125-139. Wright, A.J. (1983). The expected efficiencies of some methods of selection of components for inter-genotypic mixtures. Theor. AppL Genet. 67, 45-52. Wright, A.J. (1985). Selection for improved yield in inter-specific mixtures or intercrops. Theor. Appl. Genet. 69, 399-407. Zadoks, J. C. (1987). The function of plant pathogenic fungi in natural communities. In "Disturbance in Grasslands" (J. Van Andel, ed.), pp.201-207. Junk, Dordrecht. Zeigler, R. S., Tohme, J., Nelson, R.J., Levy, M., and Correa-Victoria, F.J. (1994). Lineage exclusion: A proposal for linking blast population analysis to resistance breeding. In "Rice Blast Disease" (R. S. Zeigler, S. A. Leong, and P. S. Teng, eds.), pp. 267-292. CAB International International Rice Research Institute, Wallingford, UK P.O. Box 933, 1099 Manila, Philippines. Zeigler, R. S., Cuoc, L. X., Scott, R. P., Bernardo, M. A., Chen, D. H., Valent, B., and Nelson, R.J. (1995). The relationship between lineage and virulence in Pyricularia grisea in the Philippines. Phytopathology 85, 443-451. Zeigler, R. S., Scott, R. P., Leung, H., Bordeos, A. A., Kumar, J., and Nelson, R.J. (1997). Evidence of parasexual exchange of DNA in the rice blast fungus challenges its exclusive clonality. Phytopathology 87, 284-294.

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8 Plant-Arthropod Interactions in Agroecosystems

D. K. Letourneau

I. Introduction: Crops as Resources As growers plan the temporal and spatial pattern of crops in their fields and make decisions about management practices to optimize the productivity of these crops, they are inadvertently designing the local resource base for the arthropod community, including herbivores and their natural enemies. This chapter focuses on ecological principles that can be applied within agroecosystem management schemes to change the quality of the crop as a resource. The aim is to reduce the colonization, growth, survival, and reproduction of phytophagous arthropods as consumers. Many of these ecological concepts of plant-arthropod interactions and consumer dynamics are derived from research over the past three decades. The 1970s produced a rich body of theory on predator-prey, parasitoid-host, and herbivore-plant interactions. The 1980s brought challenges of theory based on two trophic levels and the emergence of research on multitrophic level systems, involving interactions among plants, their herbivores, and the natural enemies of the herbivores. Critical tests of these hypotheses in the 1980s and 1990s and of island biogeography and trophic cascades theory from the 1960s have clarified the extent to which general patterns apply to specific conditions and species assemblages. This ecological knowledge of plant-arthropod interactions offers explanations for why agroecosystems are relatively vulnerable to pest irruption and can be applied in agriculture to create prophylactic conditions against pest outbreaks. The reward for Ecology in Agriculture

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effective preventative measures is an increase in marketable yields without the monetary cost, the health risks (e.g., to farmworkers and consumers), and the environmental disruption (e.g., groundwater contamination and nontarget species kills) resulting from reactive applications of insecticides and miticides. Pimentel (1986, 1993) estimates that the return per dollar invested in ecologically based cultural controls of insect pests ranges from $30 to $300 compared to an estimated $4 per $1 invested in pesticides. The extension of ecological principles to pest regulations in agroecosystems, however, is hampered in two fundamental ways. First, the nature of a "principle" is generality, but the staggering amount of diversity in habits and life histories among phytophagous arthropods defies any strict adherence to generalities. Perhaps it is time to envision, given technological advances in data management and expert systems, the collection and organization of detailed results from ecological studies on plant-arthropod interactions as a basis for making specific decisions in pest management. However, the second caveat involves the degree to which results from ecological studies in natural systems can be transferred to understanding plant-arthropod interactions in agroecosystems. Comparative studies of herbivore abundance and diversity between natural and managed habitats are rare (Barbosa, 1993). Thus, assumptions about parallels in natural and managed systems are, for the most part, untested. Therefore, I have included counterexamples and critical analyses of the evidence for applicability and transferability among systems, and I recommend the use of ecological principles to guide, not to prescribe. I have organized the chapter to emphasize plant-arthropod interactions from the plant perspective and have included explicit statements of ecological concepts, patterns, or hypotheses that have predictive value for crop plant defense. The main concepts for achieving pest management are biodiversity, integrated systems of ecological control, and heterogeneity.

II. Ecological Consequences of Economically Driven Decisions" The Grower's Perspective Growers must understand, prioritize, and juggle a complex array of information "bits" to strategically aim at maximum profits by balancing incremental costs of inputs with expected gains in marketable yields. Crop production decisions are made as growers consider a range of factors as disparate as seed prices, mechanical equipment options, marketing trends, and soil pH levels. Meanwhile, these same factors determine the attributes of the resource base for insects and mites (e.g., Zadoks, 1993), which account for approximately 13% of the species reducing yields in agricultural crops worldwide and 13% of total crop losses (Pimentel, 1993). As the

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grower considers seed prices, h e / s h e is contemplating the selection of a particular crop and crop cultivar, which in turn determines the food resource being presented to the local arthropod community. Decisions about mechanized production tools may be made in response to labor availability and other factors not directly connected to pest management, but may indirectly affect crop vulnerability to pest outbreaks in various ways, such as their effects on soil compaction, tillage schemes, crop rotation, or even dust levels on crop foliage. Marketing trends may determine harvest dates (and thus planting dates) and the phenology of the crop at harvest (e.g., harvests for fully matured corn ears or "baby" corn ears or vine-ripened versus green tomato fruits), which determines the length of time resources are available for pest populations; and soil pH levels will guide the grower in h i s / h e r decision about soil amendments, which can alter crop quality as resources for growth and survival of insects and mites. If effective chemical insecticides and miticides were as inexpensive and available as they once were, growers could continue to pay little attention to the connections between m a n a g e m e n t decisions and pest irruption. However, the past decade or so has been a time of economic stress for tens of thousands of U.S. farmers who, at a time of highest output per unit of input, have still suffered severe financial problems (Duffy, 1991). Recent surveys have shown that the majority of farmers are concerned, in the current atmosphere of incentives for reduced input costs, about reliance on chemical inputs (Duffy, 1991). One way to prevent unnecessary use of agrichemicals is to add pest outbreak prevention to the considerations used in the grower's strategic approach to crop production.

III. Exploitation Strategies: The Herbivore's Perspective Phytophagous arthropods can be found within mite families (Order Acarina) and within nine orders of insects (Coleoptera, Collembola, Diptera, Hymenoptera, Thysanoptera, Phasmida, Lepidoptera, Orthoptera, and Hemiptera) and make up more than 90% of the species in the latter four orders (Strong et al., 1984). These herbivores comprise four crosscutting categories of host plant use: (i) those that derive all of their resources from a single crop, completing their entire life history in the crop field (such as two-spotted mites, corn rootworms, and cabbage aphids); (ii) those that require diverse resources not offered by a single crop for their survival and reproduction; and, as subsets of the first two categories, (iii) arthropods that exhibit a wide host range such as the corn earworm and two-spotted mite, which can forage on many crops including corn, tomato, soybean, and cotton; and (iv) those species that are restricted to particular crops and related genera or families, such as cabbage aphids or cucumber beetles.

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Feeding biologies, dispersal ranges, host plant location mechanisms, and generation times vary considerably within these diverse groups of arthropod herbivores. Phytophagous mites and insects feed on foliage, stems, roots, fruit, and seeds in numerous ways, including chewing, rasping, sucking out the contents of plant cells, tapping into the vascular system, mining leaves or stems, and producing plant galls. Some arthropods are relatively sessile. For example, European corn borers overwinter in corn stalks and codling moths stay under the bark of apple trees, building resident populations in fields or orchards. On the other hand, many arthropods are extremely vagile, dispersing regularly over long distances and across wide areas by exploiting the ephemeral but very structured nature of air movement (Wellington, 1983). Robust herbivores and their minute parasitoids can exhibit coupled displacement in long-distance migration, as shown by the Australian plague locust, Chortoicetes terminifera Walker, and its egg parasitoid, Sceliofulgidus Crawford, which disperse independently on wind currents to the same location (Farrow, 1981). Whether an herbivore moves long or short distances to encounter its host plant, different mechanisms are used for host habitat finding, host plant location, host assessment, and host plant use. For many insects, visual cues and chemical cues are both important in this complex process of colonizing host plant patches. Once arthropods develop resident populations in crops, they can exploit the resource within a single generation per year (univoltine) or they may complete 2-12 or more generations (multivoltine) during a growing season. The diversity in feeding, movement, host finding, and life histories is underscored by the fact that ecological patterns of crop exploitation are dynamic. Each herbivore species has an evolutionary history that interacts with ecological events to produce adaptations to changes in their host plant resources. Herbivores that exploit cultivated varieties often encounter resources that differ in fundamental ways from the plants' wild relatives (see Chapter 2, this volume). Attributes that have arisen out of the selection process for high productivity and palatability of specific plant parts tend to increase the crop's suitability as a host for phytophagous arthropods. First, compared to their progenitors, crop plants can contain lower levels and simplified suites of antiherbivore defenses (Kennedy and Barbour, 1992), can possess a more uniform genetic composition, and may experience lower levels of plant stress. Second, the presentation of these plants to herbivores differs from the conditions found in most of the communities of their wild relatives in its tendency for uniformity in species composition, age distribution of the population, and structural pattern. The application of management technologies to crop fields constitutes the third level of intervention that changes the quality of crops as resources to herbivores. For example, agrichemicals effect changes in the host plant and its microenvironment. Such emergent qualifies of crop production enterprises directly or indirectly

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impact feeding, reproduction, migration, survival, and the behaviors associated with these arthropod life processes. Many of these aspects of herbivore attributes and crop habitats will be expanded in the following sections to better understand plant-arthropod interactions and the opportunities and constraints to pest management in agricultural systems.

IV. Ecological and Evolutionary Antiherbivore Strategies: The Plant's Perspective Although outbreaks of phytophagous arthropods and widespread plant injury do occur in pristine, native habitats (e.g., Wolda, 1978), plants in their native habitats have a relatively low probability of being devastated by herbivores (Mattson and Addy, 1975). The mechanisms by which plants gain protection from herbivore attack are both passive and active. I use the term "passive" to describe ways that the number of potential herbivore colonists are limited through the escape of plants in time and space. This term also serves to describe resistance to herbivores that is gained through association with other plants. Crops growing in vegetational assemblages can incur reduced herbivore attack when herbivores are drawn to an associated, preferred host or when associated plants mask the presence of the host plant to colonizing herbivores. Another form of passive defense occurs through tolerance mechanisms, which do not serve to reduce herbivory but allow the plant to sustain herbivory with relatively little impact on plant fitness (or yield). In contrast," active" mechanisms of plant defense include plant resistance traits that directly reduce herbivore performance as it uses the plant as a resource. These include antibiotic characteristics that inhibit feeding, growth, survival, or reproduction of herbivores and can be present continuously (constitutive resistance) or can occur facultatively (induced resistance) in the plant. A key characteristic of natural plant populations is their genetic and phenotypic heterogeneity. Whether plants derive protection from herbivores through passive or active mechanisms or a combination of both, individual plants tend to occur in natural habitats as a mosaic of resistance factors due to genetic variability (Whitham et al., 1984) and induced responses. Such heterogeneity inherently reduces the probability of counterresistance in rapidly evolving phytophagous arthropods and increases the durability of plant defenses over time.

A. Escape in Time Most herbaceous, early successional plants are relatively ephemeral and therefore escape discovery by herbivores and~or the buildup of damaging herbivore populations that would occur if plants were more predictable or persistent.

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For plants in general, the expectancy of being found by herbivores depends largely on patch size and temporal (or durational) stability. In natural plant communities, patch size and temporal stability for plants tend to increase with successional stage (Southwood, 1987). Feeny (1976) and Rhoades and Cates (1976) proposed that early successional plants, as relatively less apparent plants, may escape herbivore damage in space and time. However, many plants from which annual crops have been derived are early successional species, having traits characteristic to those of colonists (e.g., cole crops, carrots, and lettuce). Thus, when annual plants are selected for agricultural production, set in large monocultures, and maintained for one or more growing seasons, their "apparency" is artificially increased. Although experimental tests of the role of apparency per se in annual crop vulnerability are not available, a quick comparison of the n u m b e r of major pests on 19 annuals and 15 perennials by Hill (1987) suggests a twofold difference, on average (X = 7.9 _ 4.4 SD on annuals vs X - 3.3 _ 2.7 SD on perennials; Student's t - 2.25, P = 0.0314), between the variety of severe pest pressures on crops derived from ephemeral stock and on perennial crops. Price (1984a,b) developed a conceptual framework of resource availability categories that includes continuous, steadily renewed, and pulsing resources. Although the aim of his study was to express different probabilities of interspecific competition among insect herbivores, it serves as a useful framework for understanding the dynamics of a r t h r o p o d - c r o p synchrony (Fig. 1). For many crops in most geographical locations, growers have some flexibility in (i) crop selection from one growing season to the next, (ii) planting dates, and (iii) timing of harvest, all of which can be used to the detriment of arthropod population growth on crops as resources. 1. Crop-Pest Phenologies The n u m b e r of herbivores colonizing the crop at any given time depends in part on the absolute abundance of herbivores in the habitat and their vagility. A knowledge of pest life cycles can be used in some cropping plans to shift the synchrony of the crop, or vulnerable stages of the crop, away from peak dispersing periods for the arthropods. If a key pest is univoltine, one tactic would be to sow the crop after monitored adult flight patterns are on the wane (Fig. 1, late pulsed resource). Hessian fly damage to wheat is reduced substantially when planting is timed to follow the decline in fly populations (Buntin et al., 1990). Similarly, for lowest preharvest infestation of dent corn by Angoumois grain moths (Lepidoptera: Gelechiidae), late planting (June) is r e c o m m e n d e d (Weston et al., 1993). In contrast, multivoltine pest species tend to increase in abundance with each generation over the growing season. It may be possible to time the

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initiation of annual crops to coincide with low pest numbers, early in the season (Fig. 1, early pulsed resource). Mack and Backman (1990) showed that early planting of p e a n u t crops reduced the incidence of lesser cornstalk borer. Likewise, early sowing of sugar beet allowed the plants to reach a more resistant growth stage before virus-vectoring aphids colonized the crop (Heathcote, 1970). In a recent comparative study of commercial tomato production on organic and conventional farms in the Sacramento Valley in California, the timing of crop initiation was the single most explanatory factor for crop damage by foliage-feeding insects (Drinkwater et al., 1995; Letourneau

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et al., 1996). Reduction of photosynthetic tissue by thrips (primarily western flower thrips, Frankliniella occidentalis) was greatest in early sown tomato and damage by strip-feeding insects, primarily lepidopterans, was heaviest in late-planted fields, despite the wide range of m a n a g e m e n t practices used on the 18 organic and conventional farms (Fig. 2). Different optimal planting dates were also found for different pests in dryland cotton, with early (April) plantings suffering disproportionately high levels of thrips and boll weevil damage and later plantings having high populations of cotton leafhoppers and cotton aphids (Slosser, 1993). When pests respond differentially to planting date, the grower must devise a strategy for achieving host plant escape from herbivores based on the severity of different pests, but may also take into account the likelihood of early colonizers acting as alternate hosts for natural enemies of the main pests (eerring et al., 1988). 2. Crop Rotations Outbreak levels of crop-damaging arthropods that remain in or near the crop field from one growing season to the next can be avoided by disrupting population growth with sequential planting of host and nonhost plants. For example, the northern and western corn rootworms (Diabrotica spp., Coleoptera: Chrysomelidae), which have one generation per year in the U.S. corn belt, have become serious pests in nonrotated corn. Populations are not supported on broadleafed weeds and crops or even on grassy weeds or sorghum (Gray and Luckmann, 1994); and corn-soybean rotations have been a very effective control of these

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rootworms for more than six decades. Although rotation has been effective for soil-dwelling corn rootworms and can be a pivotal control tactic for soilborne pathogens and nematodes, most arthropod pests that can disperse long distances may be suppressed only if crop rotations are implemented on a regional basis (Finch, 1989). However, strong and widespread selection pressures, even with cultural practices such as rotation, can drive undesirable adaptations in pest populations. Levine et al. (1992) have found evidence that rotation has selected for longer dormancy periods in corn rootworm. Whereas most of the rootworms starve upon emergence in a field lacking a host plant, a portion of the population remains in diapause through the soybean crop and emerges when corn is sown again.

3. Resource Truncation Plants in natural habitats must complete their development and produce seed to maintain fitness. However, yield for many crops is not dependent on seed maturation and is not subject to the same constraints that influence the progenitors of crops in nature. Standard practice in irrigated cotton, for example, includes the application of chemical defoliants, dessicants, or plant growth regulators before the end of the growing season to cause the crop to drop the leaves and squares (buds) that act as food and shelter resources for pink bollworms, bollworms, and the boll weevil (Adkisson, 1962; Jones et al., 1990). In a similar way, early termination of the cotton crop (before November frost) in nonirrigated cotton may provide an ecologically based alternative to multiple fall pesticide applications currently mandated by the Texas Boll Weevil Eradication Program. Cotton squares and small green bolls remaining on the crop after mid-September will not mature before the final harvest, and boll weevils using these resources after mid-September have a lower incidence of mortality through the winter diapause (Montandon et al., 1994). Therefore, early harvested cotton under these conditions has comparable yields while boll weevil controls and chemical input costs (capital and environmental) are reduced. Pest phenologies and life histories determine appropriate intervention times for disrupting the resource base for pests. An example of a much shorter cycle of pulsed resources (Fig. 1) is shown by the lucerne leafroller Merophyas divulsana in New South Wales. The generation time of this multivoltine herbivore approximates that of the normal harvesting cycle of the crop, so early harvesting of the crop is a key control tactic in the management of this pest (Bishop and McKenzie, 1986). Also in Australia, sugarcane presents an example of resource truncation over a period of several years. Populations of the sugarcane soldier fly, Inopus rubriceps, increase locally from year to year on a continuous supply of stubble left in the field to produce new rattoon shoots after harvest (Samson, 1993). Periodic plowing is necessary to disrupt the resource before crop failure occurs from resident fly populations.

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B. Escape in Space There exists a species-area relationship such that the equilibrium number of species supported by an island increases with the size of the island relative to its distance from the mainland. The insular nature of cultivated areas has motivated several analogies regarding crops as islands available for colonization by arthropods (Price and Waldbauer, 1994; Strong, 1979; Simberloff, 1985). MacArthur and Wilson's (1967) dynamic equilibrium theory of island biogeography allows the prediction of colonization rates and mortality/emigration rates on a comparative basis, with respect to crop area and distance from the sources of colonizers. Although this body of theory organizes thought on the colonization process in crop fields, some impediments to its application include (i) the notion that temporal dynamics of crop fields, as frequently disturbed communities, may cause responses different from those predicted by equilibrium models; (ii) the fact that biogeographic theory does not distinguish among types of colonizers, which is critical when considering natural biological control and arrival rates of pests versus their predators (Price, 1976; Stenseth, 1981); and (iii) the current status, in which the few empirical data available on diversity, size, and distance relationships provide an insufficient basis for agricultural planning recommendations (Simberloff, 1985). Nevertheless, general predictions from theory may be extremely important in anticipating and managing plant-arthropod interactions on the landscape level in agroecosystems. 1. Isolation from Colonizer Pools On a global scale, crops have experienced a far more dramatic level of release from key herbivores than have indigenous plants growing in their natural habitats. Release from herbivore pressure in native habitats would be a relatively rare, temporary, and localized circumstance due to stochastic events. In contrast, there tends to be a gradual development of herbivore communities on crops introduced to new continents. Strong (1974) and Strong et al. (1977) traced the development of pest assemblages through time for cacao and sugarcane, respectively. In both crops, the initial numbers of herbivore species on these crops after introduction was much lower than the number of species that had exploited these crops previously in their place of origin. On a regional level, the placement of crops distant from other crop fields or closely related species can also result in reduced colonization by herbivore species, but much of the evidence for fields that are free from certain pests is anecdotal. Understandably, many ecologists and entomologists study herbivores where and when they are abundant, so data are relatively lacking for locations in which herbivore populations are absent or at extremely low levels (e.g., Nothenagle and Schultz, 1987; Price et al., 1984). However, relatively rapid colonization rates of pests from nearby sources (e.g., adjacent fields) has been documented frequently. Examples include

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the regional movement of exploding populations of whiteflies from cotton to melon and from melon to lettuce as these crops are harvested sequentially (Blua et al., 1994); the movement of chinchbugs, grasshoppers, and armyworms from small grains to nearby corn fields (Price and Waldbauer, 1994); and rapid population growth of cabbage seedpod weevils in rape within close proximity of alternate hosts and overwintering sites (Boyd and Lentz, 1994). In an explicit test of distant versus near "crop islands," Kruess and Tscharntke (1994) showed that most herbivore species colonized small red clover patches but that the abundance of these herbivores declined with greater distances from a source of colonizers. Furthermore, the number of species of parasitoids colonizing the red clover patches was significantly lower, through increased extinction rates and decreased colonization rates, as distance from the source increased. Economies of scale that dominate the agricultural sector in developed countries allow farmers to reduce unit production costs by increasing farm size and becoming more specialized. The resultant changes in crop island size over time as part of a matrix of wildlands, fallow fields, land planted in other crops, and urban areas will have widespread effects on pest-crop dynamics as crop fields expand, as particular crops intensify as profitable enterprises, and as wildlands become more fragmented. Rabb (1978) addressed appropriate research scales almost two decades ago when he criticized the propensity of single-commodity, closed system approaches to pest management in research and decision making as deficient for problems that demand attention to "large unit ecosystem heterogeneity." Ryszkowski et al. (1993) showed that landscape heterogeneity was a strong determinant of both insect biomass and species diversity. Research at the landscape level on animal movement and metapopulation dynamics using GIS will allow rigorous analyses of the effects of host plant (habitat) isolation on herbivore colonization (e.g., Kalkhoven, 1993). As theory develops in the field of conservation biology on habitat linkages for conserving endangered species and key factors in extinction, applications will accrue in the conservation of natural enemies and the suppression of pests, respectively. 2. Size-Discovery Patterns Species richness is positively correlated to size on oceanic islands. Similarly, in mainland communities, large, isolated patches of a single plant species may support more species than do small, isolated areas (Strong, 1979). Larger host islands can collect more individuals by random probability of encounter (Connor and McCoy, 1979). Furthermore, patch detection by dispersing specialist herbivores increases, in general, with size and homogeneity. Ecological tenets on island biogeography, once again, suggest that extensive monocultural production units can favor pest outbreaks. Extinction rates depend on resource availability in the system. Because crop plants are supplied to the system, or "reset" at certain intervals (Levins

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D. K. Letourneau

and Wilson, 1980), the resource base is predictable, at least for herbivores colonizing sufficiently early in the crop cycle. Because of resource availability for herbivores and delayed resource (prey/hosts) availability for natural enemies, extinction rates will be greater for parasitoids and predators discovering crop islands early in the season. In Kruess and Tscharntke's (1994) comparison of 16 red clover meadow fragments ranging in size from 300 to 800,000 m 2, the species richness of herbivores and of parasitoids and the proportion of parasitized seed weevils (Apion ochropus) were all significantly and positively correlated with "island" size. Differential resource availability for colonizing species on different trophic levels is not an explicit part of MacArthur and Wilson's model (1967), but disparities become important in pest management. Also, the equilibrium theory of biogeography does not allow for comparisons of single, large crop fields versus a network of several small fields of the same total area, but the contrasting designs are likely to differ in terms of suitability for both herbivores and biological control (Price, 1976; Altieri, 1994). C. R e d u c e Palatability or Suitability

The array of environmental factors that affect the resistance of the host to herbivore attack, in concert with genetic components of intraspecific variation in plant morphology, aUelochemistry, and nutrition, produce heterogeneity that may be central to the regulation of herbivore populations. If the "world is green," with plants making up the most obvious and readily available resource in terrestrial communities, why don't herbivores reduce it to stubble? The answer, in part, is that plants are less suitable as food than they appear to be (Strong et al., 1984). In natural systems, physical and chemical defenses as well as nutrient deficiencies present major hurdles for phytophagous arthropods in colonizing and using plants as resources (Feeny, 1990). Our current body of knowledge represents almost three decades in ecological research and provides the fundamental tools for selecting and maintaining relatively resistant crops. Like their wild progenitors, crops possessing physical or biochemical properties that reduce their attractiveness or adequacy as a food resource are relatively resistant to exploitation by herbivores. Resistance can be achieved through inherent plant traits a n d / o r modified by environmental conditions. Ecological theories of plant defense suggest that resources are allocated optimally among growth, reproduction, and protection. In evolutionary time, plants have evolved physical and chemical defensive mechanisms against herbivores, pathogens, and other plants, depending on the strength of these organisms as selective factors. If energy and materials are used exclusively for defense, then the cost of these resources is perceived as the concomitant reduction in resources available for other plant functions

8. Plant-Arthropod Interactions

251

related to fitness. If defensive structures or compounds are beneficial in other ways, such as trichomes as antidessication features, the costs of these defenses are mitigated by gains derived from multiple functions (Zangerl and Bazzaz, 1992). Theoretically, costs and benefits ofantiherbivore defense are not uniform among plant parts but vary as a function of the relative fitness value of the tissue and the relative probability that the tissue will be attacked by herbivores. Therefore, genetic defense systems in wild progenitors may be out of phase for crops whose agricultural value (yields) differs fundamentally from their fitness value (e.g., leaves or fruit versus seeds). Even when plant resistance traits are used effectively as tools for the regulation of crop pests, the combination of rapid generation time, genetic variation, and natural selection has led to the development of resistance to plant defenses among populations and species of phytophagous arthropods (Via, 1990). Because resistant crop varieties are designed to increase mortality or decrease fecundity of herbivores, they eventually select for better adapted pests that are more difficult to control. For example, the notorious greenbugs (Schizaphus graminum aphids) have been controlled since the 1940s using various lines of resistant wheat, but decade after decade new counterresistances have developed in aphid populations, making it necessary to establish alternative varieties with novel resistance traits (Wilhoit, 1992). Such counterresistance can be managed, to some extent, using knowledge of population dynamics and natural selection. An increasing amount of research effort on resistance management tactics has occurred during the past decade and prompted, in 1988, the creation of a new categorical heading: "Insecticide Resistance and Resistance Management" for indexing articles in TheJournal ofEconomicEntomology. Recommendations for maintaining susceptible individuals in the population are a direct result of population ecology.

1. PhysicalAttributes Crop varieties with morphological barriers to arthropod movement, feeding, and oviposition may incur lower levels of damage from phytophagous arthropods and produce increased yields, depending on the energetic cost of the defensive structures and resource allocations in the crop. Although morphological barriers themselves, such as spines, toughness of tissues, pubescence, and waxes (Kogan, 1994), are often derived from chemical bases, such as the overproduction of silica or lignin or the cross-linkage of lipids, the actual effect on herbivores is only through physical deterrence rather than through the olfaction or gustatory processes that characterize chemical defenses. To my knowledge there is no general theory contrasting the occurrence of physical versus chemical defenses among plant taxa. Neither are there predictive guidelines regarding target herbivore groups that respond to physical versus chemical plant defenses. Both chemical and physical resistance traits are variable in occurrence and

252

D. K. Letourneau

widespread among plant taxa. Although physical and chemical resistance traits are usually treated separately, they in fact act as a package in many cases. For example, the trichomes of wild tomato (Lycopersicum hirsutum) produce 2-tridecanone and zingiberene, which add toxicity to the basic physical deterrence of plant hairs for several arthropod pest species (Hare, 1990). Both types of defense are linked to other plant functions as part of the plant's structural attributes (e.g., stalk strength, water retention, or metabolic functions). Physical defenses may be less subject to environmental variability than are chemical constituents and are generally detectable only in close proximity when the arthropod is already in contact with the plant. Because they generally require different mechanisms of counterresistance, a combination of physical and chemical defenses can increase the durability of resistance in plants. a. Toughness Sclerophyllous leaves and bracts are tough; they resist fracturing and bending. A relatively thick cuticle and a high cell wall : cytoplasm ratio (and thus a high crude fiber:crude protein ratio) reduces their suitability for food (Specht and Rundel, 1990). They are relatively expensive to the plant but effectively deter herbivores (Turner, 1994). Although most crop plants have malacophylls (soft textured leaves), varieties with relatively tougher tissues can confer resistance against some phytophagous arthropods (Norris and Kogan, 1980). The role of leaf toughness as a significant impediment to herbivore feeding has been shown, for example, for the mustard beetle (Phaedon cochleariae) on cole crops (Tanton, 1962), the cereal leaf beetle (Oulema malanopius) on grains (Shade and Wilson, 1967), and for a wide variety of lepidopteran herbivores on maize (Bergvinson et al., 1994a). b. Trichomes Leaf surface texture of crop plants can be an extremely important determinant of its suitability for an herbivore. Plant hairs, whether multicellular or unicellular, glandular or nonglandular, straight, spiral, hooked, simple, or stellate, occur on plants in almost every family (Johnson, 1975; Levin, 1973). Leaf trichomes vary geographically within species in natural habitats, and the patterns of variation involving glandularity, which has little effect on biophysical properties of the leaf surface, suggest that herbivory may be an important selective factor for this variation among natural populations. Hooked trichomes on wild Passiflora plants successfully impale butterfly larvae as they forage (Gilbert, 1971) in much the same way that adult leafminers are trapped on resistant bean varieties (Quiring et al., 1992). Plants with dense trichomes can also deter insects by preventing the proboscis from entering the tissue, by inhibiting attachment to the plant surface (Lee et al., 1986), or by disrupting oviposition (Dimock and Tingey, 1988). Movement can be impeded, especially with sticky exudates from glandular hairs (Gibson, 1976), and some trichomes

8. Plant-Arthropod Interactions

253

are toxic (Casagrande, 1982) or produce pheromone mimics that signal insects to drop from the leaf surface (Gibson and Pickett, 1983). Trichomes are not restricted to plant foliage. Their presence on fruits can also reduce damage, as has been shown for peaches versus nectarines infested with thrips and mites (Cravedi and Molinari, 1984), and may explain differences in insect and mite infestation of kiwi fruit varieties (Tomkins and Steven, 1993). Recent studies indicate that trichome density can be increased facultatively in response to herbivore damage on leaves (Baur et al., 1991), climatic conditions (Gianfagna et al., 1992), and possibly by stem-borer damage to the meristem (Letourneau and Barbosa, 1997). I am not aware of any studies on induced trichome development in response to herbivore damage in crop plants; however, if trichome production depends on sufficient nutrient uptake (Hagen and Anderson, 1967) and compromises yields in some crops (see Agren and Schemske, 1993), facultative production may be an efficient resistance mechanism. As in virtually all plant defenses, the vast array of herbivores that come in contact with the plant include species that tolerate or prefer the trait that confers resistance generally (e.g., Webster et al., 1994). For example, Heliothis zea (corn earworm) oviposits preferentially on pubescent soybean varieties (Panda, 1979). Trichomes can also protect herbivores from their parasitoids or predators (Table I). However, in contrast to the examples of trichomes acting as barriers to natural enemy searching efficiency, Shah (1981) showed that rapid turning rates in predatory lady beetle on hirsute brassicaceous crops resulted in increased encounters with their aphid prey. c. Other Physical Barriers Vital functions in ectopic herbivores (e.g., feeding and reproduction) require attachment to the plant surface. In this regard, waxy blooms on foliage can make a plant an unsuitable host for herbivores that lack special adaptations for stability (Bodnaryk, 1992). For internal feeders, entry into the preferred tissues for feeding is critical. Structural barriers such as silicon-reinforced vascular tissue can prevent cane pith feeding by early instar lepidopterans; extremely tight husks can reduce the incidence of corn earworm damage on some corn varieties (Kogan, 1994). These types of physical barriers to herbivores may interact favorably with biological control. The herbivore's time of exposure to natural enemies, for example, can be extended by delaying herbivore entry to refugia. Structural barriers are also likely to be differentially effective for arthropods with different morphological traits (e.g., a caterpillar versus a wasp). 2. Chemical Attributes Two parallel lines of investigation of chemical defenses in plants have advanced independently: (i) Ecologists and evolutionary biologists have developed concepts of plant ecophysiology, plant-

Table I Examples of Mechanisms by which Physical or Chemical Plant Defenses Can Inhibit Biological Control

P

Enemy

Herbivore

Plant

Mechanism

Reference

Anthocorids

Breuicmyne brassicae

Deterred by waxy leaves

Way and Murdie (1965)

Encarsia fmmosa Gahan (Hymenoptera:

Trialurodes vapmariorum (Westwood) (Homoptera:

Brussels sprouts (Brassica oleracea gemmqera) (Brassicaceae) Hirsute cucumber varieties

Hulspas-Jordaan and van Lenteren (1978)

Aphelinidae) Trichogramma p-etiosum and Chlysopa rufilabris Burm. (Neuroptera: Chrysomelidae) Predaceous mites

Aleurodidae) Heliothis zea

Hirsute cotton varieties

Herbivorous mites

Ficus carica L. (Moraceae)

Coccinellids

Aphids

Hirsute potato varieties

Trichome mat hinders movement and searching efficiency Increased trichome density reduced ability for small predators to locate and destroy host/prey Glandular hairs correlated with increased o r decreased rate of prey consumption depending on predator species Reduction in adult searching time; larval mobility impaired; but these effects were attenuated in the field

Treacy et al. (1985)

Rasmy (1977), Rasmy and Elbanhawy (1974)

Obrycki and Tauber (1984)

Predaceous mites

Tetranychid mites

Apple and peach

Hyposoter exiguae (Viereck; Ichneumonidae)

Heliothis zea

Tomato

Geocoris punctipes

Anticarsia gemmatalis

Soybeans

Archytas mannoratus

Helzothzs zea

Cornsilks

Copidosoma truncatellum

Pseudoplusia includens

Soybean (Glycine max L.)

Pediobius foueolatus Campoletis sonorensis

Epilachna uarivestis Spodqptera frugiperda

Soybean Maize (Zea mays L.)

Geocoris punctipes

Heliothis zea

Chlysoperla carnea; Trichogramma sp.; Hippodaemia conuergens

-

Hypothetically, transgenic crops Tobacco

Putman and Heme (1966)

Possible role of pubescence in determining predator-prey contact rates on different plants Increased tomatine in host plant reduced adult parasitoid longeivity, size, and survival Predators attacking prey on resistant varieties had increased mortality rates Lower percentage of emergent adults Increased parasitoid development time Male-biased sex ratio Increased parasitoid development time P-Exotoxin

Dover et al. (1987) Wiseman and Isenhour (1990), Pair et al. (1985) Herbert and Harper (1986)

Trichomes and sticky exudates caused reduced searching speeds

Belcher and Thurston (1982), Elsey (1974), Rabb and Bradley (1968)

Campbell and Duffey (1979)

Rogers and Sullivan (1986)

Mannion et al. (1994) Orr and Boethel (1986)

256

D. K. Letourneau

animal interactions, and theories of coevolution among taxonomic groups, and (ii) crop scientists have established cultivars resistant to various arthropod pests and pathogens (Kogan, 1994). However, recent linkages among these complementary fields have produced insights into mechanisms of resistance, plant phylogenetic constraints on resistance traits, behavioral and physiological mechanisms of herbivore counterresistance, the role of heterogeneity in the durability of resistance, and environmental influences on plant chemical defenses. Soil management practices in agroecosystems can have cascading effects on plant chemical composition and herbivore damage. Resource allocation due to different soil amendments accounts for many aspects of primary and secondary metabolites in plants and can influence oviposition, growth rates, survival, and reproduction in the arthropods that use them as hosts. Agricultural studies that integrate soil management or fertilizer regimes with host plant resistance expression provide practical extensions of theoretical work in ecology concerning, for example, carbon:nitrogen balance, consumer dynamics, and trophic cascades. a. Secondary Metabolites Although many resistant varieties of crop plants have been developed without knowledge of the mechanisms underlying their effects on pests, plant secondary compounds are implicated in many cases. Chemical defenses are ubiquitous in plants and result from the interplay between phylogenetic constraints, past selection on ancestral types, the severity of stress caused by herbivores, pathogens and other plants, the energetic cost of defense, past and current nutrient availability to plants, and the effectiveness (value) of the defense. Compared to phytochemicals, which can act as attractants or repellents for host finding, oviposition, and feeding, visual and mechanical stimuli are often secondary (Hanson, 1983; Visser, 1986). Once feeding ensues, active resistance can occur through mechanisms in at least four categories: feeding deterrence, toxicity, digestibility reduction, and phytohormonal influences. 2,4-Dihydroxy-7-methoxy-l,4-benzoaxazin-3-1 (DIMBOA) acts as a feeding deterrent to the European corn borer (Lepidoptera: Pyralidae) and serves as a genetic constitutive defense of corn plants against this key pest (Barry et al., 1994). Resistant varieties can have an order of magnitude higher concentrations than susceptible varieties, and standard visual feeding assays are used by breeders to detect reduced feeding of first-instar larvae on whorl leaves. Alkaloids such as nicotine, glucosinolates such as sinigrin, and cyanogenic glycosides, found in tobacco, cabbage, and cassava, respectively, are acutely toxic to most herbivores (Rosenthal and Janzen, 1979). Digestibility reducing agents, in the form of condensed tannins, are found in many cultivars of cotton and are extremely potent in reducing the larval growth of H. zea and H. virescens on this crop. Phytoecdysones,

8. Plant-Arthropod Interactions

257

which can disrupt moulting processes in arthropods, are mainly restricted to ferns and gymnosperms. Of the four categories of chemical defense compounds, toxins and feeding deterrents are most common in plants from which crops have been derived. Unfortunately, no matter how effectively the antifeedant and toxic compounds function to reduce damage from most herbivores, particular arthropod species, in many cases, are adapted to tolerate the compounds and even to prefer feeding on plants that contain them. For example, one of the most bitter compounds known, cucurbitacin, acts both as a feeding deterrent and as a toxin for most insects and mites. However, cucurbitacin induces compulsive feeding behavior in adult cucumber beetles (Diabrotica spp.). Deheer and Tallamy (1991) showed that the larvae also feed more extensively on roots of the bitter varieties or when roots from nonbitter varieties are coated with cucurbitacin. Due to the presence of aromatic compounds, including terpenoids and phenylpropanoids (Berenbaum, 1990), which are active against most generalist feeders and have insecticidal properties (Lichtenstein and Casida, 1963), most species in the Apiaceae (e.g., carrot, poison hemlock, and wild parsnip) support a relatively depauperate herbivore fauna. Specialist herbivores on these plants are restricted to this family and a few closely related plant families. However, crops selected from wild progenitors in this family can have substantially lower levels of these compounds than their ancestors, allowing generalist herbivores to inflict relatively more damage in cultivation (Kennedy and Barbour, 1992). Because some of the most toxic compounds (furanocoumarins) are photoactivated and contained in vessels adjoining the major leaf veins, generalist herbivores can reduce exposure by feeding on the shaded portion of celery or skeletonizing the leaves, thus acquiring still lower concentrations of these toxic compounds (Zangerl, 1990). Thus, costs and benefits of chemically based resistance in crop plants depend on the balance between potential economic losses caused by herbivores that are controlled versus herbivores that are attracted and any physiological (yield) costs to the production or storage of defensive compounds (Kogan, 1986). Environmental factors, many of which are controlled in agricultural fields, sometimes modify the production of secondary metabolites in plants in complex ways. For example, nitrogen fertilizers can increase the net production of alkaloids, glucosinolates, and cyanogenic glycosides. However, additional potassium can decrease alkaloid production, low phosphorus encourages alkaloid production, and N only increases glucosinolates if sufficient sulfur is present in the soil (Waterman and Mole, 1989). Glucosinolates, which are a characteristic constituent of brassicaceous plants (Cruciferae), are toxic to herbivores not specialized to tolerate these secondary metabolites (Mattson and Haack, 1987). Although optimal defense theories suggest that concentration of these nitrogen-based defensive compounds

258

D. K. Letourneau

may be enhanced when plants are grown in N-rich soils (Finch, 1988), they may be "diluted" by extranormal plant productivity in fertilized soil (Wolfson, 1980). Water stress and salinity also have effects on herbivores that are difficult to predict. These conditions tend to increase alkaloids in plants but decrease other compounds, such as terpenes. In addition to soil characteristics, light levels and light quality influence C : N ratios and secondary metabolites. For example, glycoalkaloid production in potato leaves was increased with N fertilizer when the weather was cool and cloudy, but u n d e r warm and sunny conditions the crop has lower levels in fertilized than in unfertilized field plots (Nowacki et al., 1976). In another study, DIMBOA levels were higher in conditions of low UV light, but plants were more susceptible to corn borer larvae despite this increase because other phenolic compounds that control cell wall strength were inhibited (Bergvinson et al., 1994a,b). Thus, light levels may explain an increased susceptibility to folivores of greenhouse-grown corn plants or plants grown in overcast weather, despite optimal soil and moisture conditions. Crop plants often have a diverse set of chemical constituents that affect herbivores, and the flux of these chemicals is dynamic. Therefore, the results of studies showing that alkaloids are decreased with N fertilizer u n d e r warm, sunny conditions may not mean that the plants are more susceptible to herbivores u n d e r these conditions. Rhoades (1983) speculated that these plants are resource rich and may be producing an alternative, more costly defense such as proteinase inhibitors. The interaction with UV light, chemical defense (DIMBOA), and structural defense (involving phenolics) also suggests that trade-offs occur in defense mechanisms in response to extrinsic factors. Dynamic fluctuations can also occur temporally and in response to herbivore attack. Induced resistance refers to increased protective responses by plants after the plant is attacked or wounded. The reaction occurs in a relatively short time, and the elevated levels of secondary chemicals can be local or systemic (Ryan, 1983). In terms of optimality theory, these facultative defenses may incur less overall cost, especially if the probability of herbivore attack is low or extremely variable. The benefit of inducible defenses is that they do not incur direct costs unless the plant is actually attacked by an herbivore; the cost is that some degree of damage must be tolerated until the defensive compounds are produced or translocated (Zangerl and Bazzaz, 1992). Karban and Myers (1989) d o c u m e n t n u m e r o u s examples of induced host response to stress or injury, including the concentration of proteinase inhibitors in solanaceous plants and of latex in damaged cucurbits. Although the physiological mechanisms of induced resistance in grapevines are not yet known, the concept of induced resistance has been used in the m a n a g e m e n t of Pacific spider mites in vineyards

8. Plant-Arthropod Interactions

259

(Hougen-Eitzman and Karban, 1995). Inoculation of economically unimportant, herbivorous Willamette mites during shoot expansion causes a systemic resistance to subsequent infestations by Pacific spider mite pests. The amount of inducible resistance varies among cultivars. In cotton, levels of induced resistance tended to correlate directly with levels of constitutive resistance (Brody and Karban, 1992). Resistance to mites can be induced by nonspecific injury in cotton, and cross-resistance was demonstrated by Mclntyre et al. (1981). However, some induced resistance mechanisms can be quite specific, as shown by attempts to induce resistance to herbivores with inoculation of pathogens (e.g., Ajlan and Potter, 1991, 1992). Resistance traits (especially constitutive traits) that cause extremely virulent and effective resistance against a broad spectrum of potential pests may be desirable and highly marketable. Using molecular techniques, such attributes are now more possible to achieve. However, they are also the least durable option for pest management. Variably susceptible target species with many generations per year (and rapid turnover of symbionts in many arthropod herbivores) can produce counterresistant biotypes within a few years (Gallun and Khush, 1980; Dowd, 1991). Just as it is critical to manage resistance to pesticides for long-term use, we must also use our ecological and evolutionary knowledge base to manage single-factored genetic selection forces of chemical plant defenses in crops. Although current techniques in genetic modification of crop plants to incorporate resistance traits hold potential for the production of durable, multifaceted plant resistance (Gould, 1988), current research and, certainly, the first marketable products of this technology are based on strong, vertical resistance (Meeusen and Warren, 1989). Currently in the stage of seed production for commercial release in the next year, various crops, including corn, cotton, tobacco, and potato, will have resistant cultivars that contain the bacterial gene responsible for producing the toxic glycoprotein of Bacillus thuringiensis, a pathogen of arthropods. This 6 endotoxin is extremely effective in reducing growth and survivorship in lepidopterans (e.g.,Jenkins et al., 1993), and virulent strains of B. thuringiensis have been sought for gene extraction in this process. Benedict et al. (1993) showed 0.1 MT N ha -1 year -1 (Table I), it is easy to see why continuous c r o p p i n g m e v e n in the absence of other losses that can be of a similar m a g n i t u d e ~ r e q u i r e s exogenous nitrogen and why soil nitrogen pools are typically depleted substantially following only 30-40 years of crop production (Haas et al., 1957; Bauer and Black, 1981; Paustian et al., 1995). Moreover, only a portion of the 3-15 MT N ha -1 present prior to cultivation is actually m i n e r a l i z a b l e ~ m u c h of it will be in passive or

352

G. Philip Robertson Table I Typical Nitrogen Extraction Rates for Major Row Crops under High Yield Conditions a

Crop

Tissue

Alfalfa

Above ground

Maize

Yield (MT/ha)

% N

Total N (kg/ha)

9.0

2.8

252

Grain Residue

10.0 9.0

2.6 0.7

260 63

Soybeans

Grain Residue

2.8 5.4

6.3 0.9

176 49

Wheat

Grain Residue

5.4 6.0

2.0 0.8

108 48

Rice

Grain Residue

7.9 10.0

1.8 0.5

142 50

Cotton

Lint and seed Residue

4.2 5.0

2.9 1.3

122 65

Potatoes

Tubers Residue

56.0 5.0

0.3 1.8

168 90

Sorghum

Grain Residue

9.0 5.0

3.0 0.7

270 35

Sugar beets

Roots Residue

68.0 36.0

0.2 0.4

136 144

Sugarcane

Stalks Residue

112.0 50.0

0.1 0.2

112 100

a From Olson and Kurtz (1982) and Robertson and Rosswall (1986).

resistant soil organic matter fractions that turn over on the order of centuries or millennia (Juma and Paul, 1984; Paustian et al., 1992). Typically, exogenous nitrogen is supplied as anhydrous ammonia, urea, or some other form of synthetically fixed nitrogen (Jones, 1982; Neeteson, 1995), as organic nitrogen in the form of m a n u r e or waste sludge (e.g., Baldock and Musgrave, 1980), a n d / o r as nitrogen biologically fixed either by the crop itself (in the case of a grain or forage legume) or by a preceding cover crop such as the winter annual Vigna villosa (e.g., Ebelhar et al., 1984; Harris et al., 1994). Some exogenous nitrogen also arrives in precipitation, though typically values are small (ca. 10 kg N ha -a year -a) relative to crop needs, as are amounts of N2 fixed by associative and free-living N2 fixers. The a m o u n t of nitrogen removed in harvested biomass is also a function of the crop's nitrogen use efficiency (NUE). NUE is the efficiency with which carbon is fixed relative to available nitrogen. Operationally it is defined as plant tissue C:N ratio or plant nitrogen concentration: Plants with a higher C:N ratio (or lower N concentration) are more nitrogen

10. Nitrogen Use Efficiency

353

efficient (cf. Chapter 2, this volume). In natural populations NUE appears to be a well-characterized response to a limited nitrogen supply. Evidence for this comes mainly from studies of noncultivated ecosystems in which it appears that nitrogen is used more efficiently--i.e., NUE is higher--where it is less available. Inferential evidence includes changes in litterfall C:N ratios along nitrogen availability gradients (e.g., Boerner, 1984; Birk and Vitousek, 1986). Experimental evidence dates from Turner's (1977) work showing increased C" N ratios in the litterfall of Douglas fir fertilized with sugar to immobilize available soil nitrogen and from Shaver and Melillo's (1984) work showing lower C:N ratios in marsh grasses following nitrogen fertilization. In annual crops NUE shows similar trends: Nitrogen fertilization generally leads to lower whole plant C:N ratios as crop yield begins to fail to respond to added N above some near-saturating level. In Fig. 4, for example, the response of maize to added nitrogen was greatest between 0 and 112 kg ha -1 N addition, falling to little or no additional response beyond 224 kg N ha -1 (Broadbent and Carlton, 1978). This means that for most crops nitrogen demands increase disproportionately with yield--in this case (Fig. 3) the final 20% yield increase required 50% more fertilizer N.

III. Matching Nitrogen Availability to Demand A. Synchrony between Nitrogen Supply and Demand Synchrony between nitrogen release from either SOM or fertilizer and the demand for nitrogen by plants is a critical component that controls (a) Grain yield

(MT ha-1) ..

(b) Biomass yield 12-,- 24 | 0.78 %N / / (C:N = 64~"~/

//~,1.25%N

~6+12

600

300

N applied (kg ha-1)

0

9

I

150

N uptake (kg ha -1)

I

300

Figure 4 The response of corn (maize) to nitrogen fertilizer. (a) Grain yield response to fertilization rate; (b) total plant biomass as a function of nitrogen uptake. Dashed lines represent the minimum and maximum nitrogen use efficiencies, i.e., the amounts of biomass produced per kilogram N taken up at low and high fertilization rates. Data from Broadbent and Carlton (1978), after Loomis and Conner (1992).

354

G.

Philip Robertson

systemwide nitrogen use efficiency and thus can strongly affect nutrient retention. In mixed-species native communities and in many cropped perennial systems there will be few times during the year when soil microbial activity does not coincide with periods of at least some plant uptake. In systems cropped to annual monocultures, on the other hand, this synchrony may be largely absent. Most grain crops, for example, are part of the ecosystem for only 12-16 weeks, and for only a few weeks of this period will biomass be accumulating at a significant rate. During the grand phase of vegetative growth of corn, for example, nitrogen can be taken up at the astonishing rate of 4 kg N ha -a day -1, but uptake is only sustained at this rate for 3 or 4 weeks and falls to nil within the following 2 or 3 weeks (Olson and Kurtz, 1982). This matches rather poorly the much longer periods during which soil temperature and moisture will be sufficient to support microbial activity. During these periods microbes continue to mineralize nitrogen from crop residue and other SOM pools, and this asynchrony can contribute to a large potential for nitrogen loss and a correspondingly low systemwide NUE (Fig. 5). Asynchrony between nutrient supply and plant d e m a n d can in some cases be ameliorated by other attributes of the system. If, for example, soil water flux is low prior to plant growth, then not much nitrogen will be lost by leaching, and if denitrification is equally low then soil nitrate may remain available for crop uptake later. Likewise, if soil carbon remains available prior to plant growth, microbes may reduce nitrogen loss by immobilizing

Figure 5 Asynchronybetween nitrogen supply (from mineralized soil organic matter and fertilizers) and the demand for nitrogen by plants in a hypothetical north temperate annual cropping system. The shaded area represents the period during which the system is especially vulnerable to nitrogen loss via leaching and denitrification.

10. Nitrogen Use Efficiency

355

springtime nitrogen in microbial biomass, prior to releasing it later in the season as labile carbon stores are depleted. Asynchrony can also be buffered by serial intercrops that temporarily immobilize nitrogen. In temperate regions winter annuals such as vetch (Vigna spp.) or some native weeds may be particularly well suited in this regard because they can begin growth in early fall prior to crop senescence, lay dormant over winter, then accumulate mineralized or newly fixed nitrogen rapidly prior to their killing before crop planting the following spring. If properly managed, the nitrogen accumulated should eventually be available to the crop during its 6- to 8-week growth phase (Harris et al., 1994). Theoretically, as long as moisture conditions are favorable, this cover crop nitrogen could be available to the target crop within the same growing season: Nitrogen mineralization within a 25-cm-deep A horizon (with a bulk density as above) must sum to 1.3 mg g-1 day-1 N to meet crop nitrogen needs of 4-6 kg ha -1 day -1 during the target crop's period of grand vegetative growth (Olson and Kurtz, 1982). This rate of N mineralization is well within the range of mineralization rates for most forest and prairie soils of 1-4 mg g-1 day -1 N under favorable moisture and temperature conditions (e.g., Birch, 1960; Keeney, 1980; Robertson, 1982). Other mechanisms might also be used to buffer asynchrony in specific systems. For example, many highly weathered tropical soils have a net positive charge (Uehara and Gillman, 1981) and this anion exchange capacity could temporarily retain mineralized nitrogen that might otherwise be lost as leached NO3- (Sollins et al., 1988; Matson et al., 1987). Nitrification inhibitors have been developed for a similar p u r p o s e ~ t o protect mineralized nitrogen from leaching--and have been used with mixed success (Meisinger et al., 1980). By and large, however, asynchrony in cropping systems has not been addressed in a comprehensive manner, and it deserves serious attention where system wide NUE is an important management goal.

B. Spatial Coincidence Equal to the importance of ensuring that soil nitrogen availability and uptake are well synchronized is the concept of spatial symmetrymensuring that N availability and uptake are well matched spatially. Managementm particularly the management of row crops--does not necessarily result in a spatial arrangement of plants and resources within a field that are well matched, and a poor match will correspondingly reduce systemwide NUE. The spatial variability of soil resources occurs at a number of scales, ranging from the sub-mm scale of the rhizosphere to the 10 s km scale of regional landscapes (Robertson and Gross, 1994). From a local management perspective only two of these scales are relevantmvariability associated with row spacing, i.e., row-interrow heterogeneity, and variability associated

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with field-scale heterogeneity, i.e., historical features of the landscape that can lead to an uneven distribution of soil resources across individual fields. Row-interrow effects on nutrient availability have been recognized for decades (e.g., Linn and Doran, 1984; Klemedtsson et al., 1987), and a number of management strategies take these differences into consideration to increase both water and nutrient use efficiencies of row crop systems. Such strategies range from drip irrigation in vegetable, citrus, and sugarcane to banding fertilizer a n d / o r herbicides within crop rows. Placing fertilizer within crop rows, rather than broadcasting or injecting it indiscriminately, typically increases fertilizer use efficiency substantially (e.g., Malhi and Nyborg, 1985). Other techniques can also rearrange row-interrow nutrient availability. Ridge tillage, for example, an important soil management technique for many low-input farmers in the U.S. Midwest (NRC, 1989), is a tillage technique whereby spatial asymmetry is minimized by periodically mounding the between-row Ap horizon into semipermanent ridges into which the crop has been planted. This appears to effectively concentrate labile organic matter and soil biotic activity within the rows, achieving the same effect as fertilizer banding. Spatial heterogeneity at larger scales is also emerging as a management issue. Evidence is accumulating to suggest that soil nitrogen availability is highly variable in natural communities, with variable patches of fertility-e.g., higher soil organic matter levels or higher rates of potential nitrogen mineralization--occurring within fields at scales that can affect individual plants (e.g., Robertson et al., 1988; Hook et al., 1991). One might expect conversion to agriculture to remove this patchiness where it is not related to landscape-level geomorphological features such as slope position, but this does not appear to be the case. Rather, long-term cultivation appears to simply attenuate and enlarge precultivation fertility patches (Robertson et al., 1993), thus underscoring the persistence of biological legacies in even agricultural ecosystems (Franklin and Forman, 1987; Magnuson, 1990). Whether the result of biological or geomorphologic processes, o r - - m o r e likely--some combination of the two, field-scale soil variability (e.g., Fig. 6) appears to be a major feature of most cropping systems (Webster, 1985; Trangmar et al., 1985; Aiken et al., 1991; Dessaint et al., 1991; Robertson et al., 1997). This knowledge has led to the development of soil-specific crop management techniques (e.g., Mulla, 1993) that allow crop inputs to be applied at variable rates across individual fields. This approach holds great promise for better matching crop inputs to actual needs, and thus great promise for improving systemwide NUE. Consider, as a simple example, differences in plant productivity across a 100-ha corn field. It is likely-based on what we now know about spatial variability--that across perhaps 25% of the field maximum yields will be achieved with N inputs of 100 kg ha -a N, across another 50% yields will respond to as much as 140 kg ha -1

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Figure 6 The variability of soil nitrogen availability (nitrogen mineralization potentials) across a 0.5-ha field cropped for decades in southwest Michigan. From Robertson et al. (1993).

N, and across the remaining patches of low fertility yields will respond to 180 kg ha -1 N. Standard management practices designed to maximize yield would proscribe fertilization for the lowest common denominator, i.e., as much as 180 kg ha -1 N across the entire fieldmdespite the fact that only 25 % of the field will respond to this level of fertilization. Over the remaining 75% of the field some 40-80 kg ha -1 N will be ignored by the crop and thus is highly likely to be lost. An agronomic approach that allows rates of

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fertilizer application across this field to vary by geographic position from 100 to 180 kg ha -] N will substantially decrease the nitrogen available for total field loss. The direct economic benefit will likely be minor at least for the next decade or two--fertilizer is currently inexpensive and the cost of the technology required to implement site-specific farming practices is still prohibitive for most p r o d u c e r s - - b u t the environmental benefit could be substantial.

IV. Major Pathways of Nitrogen Loss from Cropping Systems Nitrogen not removed in harvest is lost through three major pathways in most row-crop ecosystems: fire, leaching, and denitrification. Other pathways of loss can be important in specific systems or climates but are less important in general because of improved crop management practices. Nitrogen losses from erosion and runoff, for example, can still be high in some cropping systems but have been minimized elsewhere by the adoption of conservation tillage and sound residue management techniques. Protection from fire, leaching, and denitrification, however, appears to be more difficult to implement, though probably more often because of economic or management trade-offs than because of a lack of agronomic knowledge. A. Fire Fire has historically contributed to nitrogen losses in traditional bushfallow rotation systems, and fire remains an important loss vector in many parts of the tropics. Robertson and Rosswall (1986), for example, estimated that in 1978 in West Africa, 5.5 X 109 kg N was lost annually from mainly mid-successional forests cleared for the crop phase of shifting cultivation. Annual residue burning during this phase and from continuous cultivation systems can also remove substantive amounts of nitrogen from the local system. In West Africa, ca. 253 x 10 6 kg N year -x was volatilized by fire from all annual crops in 1978, a value that is not far from the 870 X 106 kg N estimated to have been removed from these cropping systems in primary yield. Burning losses from individual crops range widely owing to crop-specific management practices and residue nitrogen contents. Losses from West African sorghum summed to 43 x 10 6 kg N with 152 X 10 6 kg N removed in yield, whereas burning losses from cassava were less than 0.1 X I 0 6 vs. 43 X 10 6 kg N removed in yield. Even in developed economies with fully mechanized agriculture, residue burning remains a conventional agronomic practice in specific situations, usually for pathogen control. For example, in South Australia and Kansas burning is used to control take-all

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disease in continuous wheat rotations, and in Texas and California it has been common to burn lowland rice residue.

B. Leaching Nitrogen losses to leaching are important in all cropping systems in which precipitation exceeds actual evapotranspiration (AET), i.e., in all systems with water flow through the solum. In semiarid cropping systems leaching may thus occur only rarely, and this may also be the case in more humid regions during the growing season--in the northern United States, for example, growing season AET is often sufficient to keep most rainwater from percolating through the soil profile and thus sufficient to keep leachable nitrogen within the roofing zone (e.g., Allison, 1973). Outside of the growing season, however, when AET is low relative to precipitation and when precipitation remains moderately high (ca. 75 mm month-I), leaching losses can be high (e.g., Chichester, 1977). This can be especially true in the fall and spring when soil nitrate pools are also moderately high (ca. 5-10/zg N gsoi1-1) from a combination oflow plant uptake and the ongoing mineralization of soil organic matter nitrogen while soil temperatures and moisture are sufficient to support microbial activity. Actual amounts of nitrogen leached from the pool of available nitrate (NOi) are a complex function of the amount of water that moves through the profile and its path and residence time--controlled largely by the soil's pore geometry and aggregate structure. Water that moves quickly through a profile may do so primarily through macropores and may thus pick up very little of the nitrate in smaller pores and inside soil aggregates (e.g., Thomas and Phillips, 1979; Helling and Gish, 1991; Smucker et al., 1995). Slower moving wetting fronts may, on the other hand, spend sufficient time in the profile to equilibrate with micropore and intraaggregate spaces that may contain high concentrations of nitrate from high rates of microbial activity and prior protection from the fast-moving wetting fronts. These slower-moving fronts may thus leach proportionately more nitrogen from the system. There is a large body of literature regarding nitrogen leaching at the plot, field, and landscape scales, mostly dating from the 1970s when health concerns caught up with widespread fertilizer use (see reviews in Singh and Sekhon, 1979; Burden, 1982; Keeney, 1982; Legg and Meisinger, 1982; Magee, 1982; Hallberg, 1989). In general, reported studies have delineated many of the important interrelationships among the matrix of factors that regulate leachingmclimate, soil, crop, agronomic management practices, and landscape position--and have fueled the development of quantitative models for predicting leaching losses from cropped ecosystems in general (e.g., Godwin and Jones, 1992; Tanji and Nour el Din, 1992; Paustian et al., 1992). Many of these models do an excellent job of predicting leaching

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losses under specific conditions, but it is clear from their performance under other conditions and in other systems that our understanding of leaching losses at the ecosystem level is still incomplete. C. Denitrification

Denitrification is the conversion of soil nitrate to the nitrogen gases N20 and N2 by a diverse array of bacteria that use nitrate as a terminal electron acceptor in the absence of oxygen. The importance of this process as a pathway of N loss in upland cropping systems is evident primarily from mass balance studies, in which denitrification is assumed to equal the difference between known inputs and harvest plus leaching outputs (e.g., Allison, 1953; Frissel, 1977; Legg and Meisinger, 1982; Paustian et al., 1990). Not until the development of a technique for studying in situ denitrification directly--using acetylene to block N20 reductase (Yoshinari et al., 1977)m was the importance of this pathway fully appreciated. Various studies have since proceeded to confirm the magnitude of losses estimated from mass balance approaches and to identify the mechanisms whereby denitrification can be active even in well-drained soils. It is now well accepted that denitrification can occur wherever available carbon, nitrate, and low oxygen concentrations co-occur--in aggregates (e.g., Sexstone et al., 1985a), soil organic matter particles (e.g., Parkin, 1987), and in bulk soil following precipitation events. Cultivation can further favor denitrification via its effects on soil bulk density, infiltration rates, and soluble C levels. Field estimates of denitrification rates range from nil to >100 kg N ha -1 year -1 in different upland cropping systems (von Rheinbaben, 1990; Aulakh et al., 1992; Peoples et al., 1995), a range similar to that of leaching losses. In general, annual rates appear to be on the order of 20-50 kg N ha -1 year -1. As a proportion of total N loss, the importance of denitrification relative to leaching losses appears to range from no leaching with moderate denitrification, denitrification and leaching about equal, to moderate leaching with no denitrification (e.g., Jones et al., 1977; Winteringham, 1980). Part of the difficulty of m e a s u r i n g - - a n d therefore of u n d e r s t a n d i n g - denitrification sufficiently well to accurately model the process at a field scale is related to denitrification's high spatial (e.g., Folorunso and Rolston, 1984; Robertson et al., 1988) and temporal (e.g., Sexstone et al., 1985b; Parsons et al., 1991) variability in most ecosystems. Perhaps because of this variability, minimizing denitrification losses has not been a specific target of management techniques to date except in lowland rice production, where denitrification is known to represent a very high proportion of nitrogen loss.

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V. Management to Maximize Nitrogen Use in Row-Crop Ecosystems Strategies to maximize nitrogen use in row-crop ecosystems must necessarily concentrate on nitrogen retention. For some cropping systems--in particular for low-yield or low-fertility systemsmour understanding of the processes involved and their major field-level controls is probably sufficient to allow the design of nitrogen-efficient rotations. This is not the case for most high-yield systems, however, in which an enormous amount of nitrogen is made available to the crop over a very short-term period of rapid growth. In these systems, making 100-200 kg N ha -1 available over a 6- to 8-week period without saturating the system with excess nitrogen remains a substantial challenge. The principle barriers to efficient nitrogen use in high-yield cropping systems are both economic and scientific. From a scientific standpoint, we lack basic knowledge of the ecological interactions in soil that regulate the seasonal timing of nitrogen release from organic matter. We also lack knowledge about the field-level controls on important pathways of lossm notably about controls on denitrification and leaching, and in particular on ways in which they interact. From an agronomic standpoint, in some cases minimizing nitrogen loss will be easy and relatively inexpensive. Devising for tropical regions a means for residue control other than burning can save as much as a third of the nitrogen typically removed in grain yields for many crops. The emerging adoption of new technology that allows crop inputs to be applied differentially across individual fields can help to better match crop demands for nitrogen with the supply of fertilizer N, thereby reducing excess application. On the other hand, devising a cover crop or residue management strategy that can help to synchronize soil nitrogen availability with nitrogen release from soil organic matter may first require the basic ecological knowledge noted previously. In many regions, however, the implementation of nitrogen-efficient cropping practices may ultimately depend on economic factors. Until the cost of nitrogen fertilizer increases, or until the environmental costs that are now externalized are made more direct, there may be little incentive for growers to adopt nitrogen conservation strategies that require additional expense or the management of additional information. To summarize, agronomists today have many strategies at their disposal for designing nitrogen-efficient cropping systems, and, with the development of new knowledge about ecological interactions in cropping systems, will have additional strategies in the coming years. The implementation of

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these strategies will not be cost-free, however, and may require marketplace a n d s o c i e t a l p r e s s u r e s in o r d e r to b e e n a c t e d .

Acknowledgments I thank P. L. Ambus, T. T. Bergsma, J. C. Boles, and M. A. Cavigelli for insightful comments on the manuscript and for helpful discussions during its preparation; L. E. Jackson, R. R. Harwood, and an anonymous reviewer also made many helpful comments on an earlier draft. Funding for this contribution was provided by the NSF LTER Program and the Michigan Agricultural Experiment Station.

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Ebelhar, S. A., Frye, W. W., and Blevins, R. L. (1984). Nitrogen from legume cover crops for no-tillage corn. Agron. J. 76, 51-55. Fee, R. (1995). Nitrogen prices ready to rise. Successful Farming 98, 11. Folorunso, O. A., and Rolston, D. E. (1984). Spatial variability of field-measured denitrification gas fluxes. Soil Sci. Soc. Am. J. 48, 1214-1219. Food and Agriculture Organization (FAO) (1945-1992). "Fertilizer Yearbooks" (annual issues). FAO, Rome. Francis, C. A., and Clegg, M. D. (1990). Crop rotations in sustainable agricultural systems. In "Sustainable Agricultural Systems" (C. A. Edwards, R. Lal, P. Madden, R. H. Miller, and G. House, eds.), pp. 107-122. Soil and Water Conservation Society, Ankeny, IA. Franklin, J. F., and Forman, R. T. T. (1987). Creating landscape patterns by forest cutting: Ecological consequences and principles. Landscape Ecol. 1, 5-18. Frissel, M.J. (1977). Cycling of mineral nutrients in agricultural ecosystems. Agro-Ecosystems 4, 1-354. Godwin, D. C., and Jones, C. A. (1992). Nitrogen dynamics in soil plant systems. In "Modeling Plant and Soil Systems" (J. Hanks, andJ. T. Ritchie, eds.), pp. 287-322. American Society of Agronomy, Madison, WI. Haas, H. J., Evans, C. E., and Miles, E. F. (1957). Nitrogen and carbon changes in Great Plains soils as influenced by cropping and soil treatments. USDA Technical Bull. No. 1164. Hallberg, G. R. (1989). Nitrate in ground water in the United States. In "Nitrogen Management and Ground Water Protection" (R. F. Follett, ed.). Elsevier, New York. Harris, G. H., Hesterman, O. B., Paul, E. A., Peters, S. E., and Janke, R. R. (1994). Fate of legume and fertilizer 15Nin a long-term cropping systems experiment. Agron.J. 86,910-915. Hart, S. C., Stark, J. M., Davidson, E. A., and Firestone, M. I~ (1994). Nitrogen mineralization, immobilization, and nitrification. In "Methods of Soil Analysis: Part 2 Microbiological and Biochemical Properties" (J. M. Bigham and S. H. Mickelson, eds.), pp. 985-1018. Soil Science Society of America, Madison, WI. Harwood, R. R. (1990). A history of sustainable agriculture. In "Sustainable Agricultural Systems" (C. A. Edwards, R. Lal, P. Madden, R. H. Miller, and G. House, eds.), pp. 3-19. Soil and Water Conservation Society, Ankeny, IA. Helling, C. S., and Gish, T.J. (1991). Physical and chemical processes affecting preferential flow. In "Preferential Flow Proceedings of the National Symposium, Dec. 1991, Chicago" (T. J. Gish and A. Shirmohammadi, eds.), pp. 77-86. Hook, P. B., Burke, I. C., and Lauenroth, W. K. (1991). Heterogeneity of soil and plant N and C associated with individual plants and openings in North American shortgrass steppe. Plant Soil 138, 247-256. Jones, M. B., Delwiche, C. C., and Williams, W. A. (1977). Uptake and losses of 15N applied to annual grass and clover in lysimeters. Agron. J. 69, 1019-1023. Jones, u. s. (1982). "Fertilizers and Soil Fertility." Prentice Hall, New York. Juma, M., and Paul, E. A. (1984). Kinetic analysis of soil nitrogen mineralization in soil. Soil Sci. Soc. Am. J. 48, 753-758. Keeney, D. R. (1980). Prediction of soil nitrogen availability in forest ecosystems: A literature review. For. Sci. 26, 159-171. Keeney, D. R. (1982). Nitrogen management for maximum efficiency and minimum pollution. In "Nitrogen in Agricultural Soils" (F. J. Stevenson, ed.), pp. 605-650. American Society of Agronomy, Madison, WI. Klemedtsson, L., Berg, M., Clarholm, J., Schnurer, J., and Roswall, T. (1987). Microbial nitrogen transformations in the root environment of barley. Soil Biol. Biochem. 19, 551-558. Ladd, J. N., and Jackson, R. B. (1982). Biochemistry of ammonification. In "Nitrogen in Agricultural Soils" (F. J. Stevenson, ed.), pp. 173-228. American Society of Agronomy, Madison, WI.

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Legg, J. O., and Meisinger, J.J. (1982). Soil nitrogen budgets. In "Nitrogen in Agricultural Soils" (F. J. Stevenson, ed.), pp. 503-566. American Society of Agronomy, Madison, WI. Linn, D. M., and Doran, J. W. (1984). Effect of water-filled pore space on CO2 and N20 production in tilled and non-tilled soils. Soil Sci. Soc. Am. J. 48, 1267-1272. Loomis, R. S., and Connor, D.J. (1992). "Crop Ecology: Productivity and Management in Agricultural Systems." Cambridge Univ. Press, Cambridge, UK. Magee, P. N. (1982). Nitrogen as a potential health hazard. Philos. Trans. R. Soc. London. B 296, 241-248. Magnuson, J. J. (1990). Long-term ecological research and the invisible present. BioScience 40, 495-500. Malhi, S. S., and Nyborg, M. (1985). Methods of placement for increasing the efficiency of nitrogen fertilizers applied in the fall. Agron. J. 77, 27-32. Matson, P. A., Vitousek, P. M., Ewel, J. J., Mazzarino M. J., and Robertson, G. P. (1987). Nitrogen cycling following land clearing in a premontane wet tropical forest near Turrialba, Costa Rica. Ecology 68, 491-502. Meisinger, J.J., and Randall, G. W. (1995). Estimating nitrogen budgets for soil-crop systems. In "Managing Nitrogen for Groundwater Quality" (R. F. Follett, D. R. Keeney, and R. M. Cruse, eds.), pp. 85-124. Soil Science Society of America, Madison, WI. Meisinger, J. J., Randall, G. W., and Vitosh, M. L. (eds.) (1980). "Nitrification Inhibitorsm Potentials and Limitations." American Society of Agronomy, Madison, WI. Mulla, D.J. (1993). Mapping and managing spatial patterns in soil fertility and crop yield. In "Soil Specific Crop Management" (P. C. Robert, R. H. Rust, and W. E. Larson, eds.), pp. 15-26. American Society of Agronomy, Madison, WI. National Research Council. (NRC) (1989). "Alternative Agriculture." National Academy Press, Washington, DC. Neeteson, J. J. (1995). Nitrogen management for intensively grown arable crops and field vegetables. In "Nitrogen Fertilization and the Environment" (P. E. Bacon, ed.), pp. 295325. Dekker, New York. Oakley, R. A. (1925). The economics of increased legume production. J. Am. Soc. Agron. 17, 373-389. Olson, R. A., and Kurtz, L. T. (1982). Crop nitrogen requirements, utilization and fertilization. In "Nitrogen in Agricultural Soils" (F.J. Stephenson, ed.), pp. 567-604. American Society of Agronomy, Madison, WI. Parkin, T. B. (1987). Soil microsites as a source of denitrification variability. Soil Sci. Soc. Am. J. 51, 1194-1199. Parsons, L. L., Murray, R. E., and Smith, M. S. (1991). Soil denitrification dynamics: Spatial and temporal variations of enzyme activity, populations, and nitrogen gas loss. Soil Sci. Soc. Am. J. 55, 90-95. Paustian, K., Andren, O., Clarholm, M., Hansson, A. C., Johansson, G., Lagelof, J., Lindberg, T., Pettersson, R., and Sohlenius, B. (1990). Carbon and nitrogen budgets of four agroecosystems with annual and perennial crops, with and without N fertilization. J. Appl. Ecol. 27, 60-84. Paustian, K., Parton, W.J., and Persson, J. (1992). Modeling soil organic matter in organicamended and nitrogen-fertilized long-term plots. Soil Sci. Soc. Am. J. 56, 476-488. Paustian, K., Robertson, G. P., and Elliott, E. T. (1995). Management impacts on carbon storage and gas fluxes (CO2, CH4) in mid-latitude cropland and grassland ecosystems. In "Soil Management and Greenhouse Effect" (R. Lal,J. Kimble, E. Levine, and B. A. Stewart, eds.), pp. 69-84. CRC Press, Boca Raton, FL. Peoples, M. B., Mosier, A. R., and Freney, J. R. (1995). Minimizing gaseous losses of nitrogen. In "Nitrogen Fertilization in the Environment" (P. E. Bacon, ed.), pp. 565-602. Dekker, New York. Robertson, G. P. (1982). Nitrification in forested ecosystems. Philos. Trans. R. Soc. London 296, 445-457.

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Robertson, G. P., and Gross, K. L. (1994). Assessing the heterogeneity of belowground resources: Quantifying pattern and scale. In "Plant Exploitation of Environmental Heterogeneity" (M. M. Caldwell and R. W. Pearcy, eds.), pp. 237-253. Academic Press, New York. Robertson, G. P., and Rosswall, T. (1986). Nitrogen in West Africa: The regional cycle. Ecol. Monogr. 56, 43-72. Robertson, G. P., Huston, M. A., Evans, F., and Tiedje, J. M. (1988). Spatial variability in a successional plant community: Patterns of nitrogen availability. Ecology 69, 1517-1524. Robertson, G. P., Crum, J. R., and Ellis, B. G. (1993). The spatial variability of soil resources following long-term disturbance. Oecologia 96, 451-456. Robertson, G. P., Klingensmith, K. M., Klug, M.J., Paul, E. A., Crum, J. C., and Ellis, B. G. (1997). Soil resources, microbial activity, and plant productivity across an agricultural ecosystem. Ecol. Appl. 7, 158-170. Sexstone, A.J., Revsbech, N. P., Parkin, T. P., and Tiedje, J. M. (1985a). Direct measurement of oxygen profiles and denitrification rates in soil aggregates. Soil Sci. Soc. Am.J. 49, 645-651. Sexstone, A.J., Parkin, T. P., and Tiedje,J. M. (1985b). Temporal response of soil denitrification rates to rainfall irrigation. Soil Sci. Soc. Am. J. 49, 99-103. Shaver, G. R., and Melillo,J. M. (1984). Nutrient budgets of marsh plants: Efficiency concepts and relation to availability. Ecology 65, 1491-1510. Singh, B., and Sekhon, G. S. (1979). Nitrate pollution of groundwater from farm use of nitrogen fertilizers: A review. Agric. Environ. 4, 207-224. Soderlund, R., and Svensson, B. H. (1976). The global nitrogen cycle. In "Nitrogen, Phosphorus and Sulphur--Global Cycles" (B. H. Svensson and R. Soderlund, eds.), Ecological bull., pp. 23-74. Stockholm, Sweden. Smucker, A. J. M., Richner, W., and Snow, V. O. (1995). Bypass flow via root-induced macropores (RIMS) in subirrigated agriculture. In "Clean Water, Clean Environment for the 21st Century Conf. Proc. Vol. III: Practices, Systems, and Adoption, Kansas, City, KS," pp. 255-258. Sollins, P., Robertson, G. P., and Uehara, G. (1988). Nutrient mobility in variable- and permanent-charge soils. Biogeochemistry 6, 181-199. Tanji, K. K., and Nour el Din, M. (1992). Nitrogen solute transport. In "Modeling Plant and Soil Systems" (J. Hanks andJ. T. Ritchie, eds.), pp. 341-364. American Society of Agronomy, Madison, WI. Thomas, G. W., and Phillips, R. E. (1979). Consequences of water movement in macropores. J. Environ. Qual. 8, 149-152. Trangmar, B., Yost, R., and Uehara, G. (1985). Application of geostatistics to spatial studies of soil properties. In "Advances in Agronomy" (N. C. Brady, ed.), pp. 45-94. Academic Press, New York. Turner, J. (1977). Effect of nitrogen availability on nitrogen cycling in a douglas-fir stand. For. Sci. 23, 307-316. Uehara, G., and Gillman, G. (1981). "The Mineraology, Chemistry and Physics of Tropical Soils with Variable Charge Clays." Westview Press, Boulder, CO. Vitousek, P. M., and Matson, P. A. (1993). Agriculture, the global nitrogen cycle and trace gas flux. In "The Biogeochemistry of Global Change: Radiatively Active Trace Gases" (R. Oremland, ed.), pp. 193-208. Chapman & Hall, New York. von Rheinbaben, W. (1990). Nitrogen losses from agricultural soils through denitrification--A critical evaluation. Z. Pflanzenernahr. Bodenk 153, 157-166. Webster, R. (1985). Quantitative spatial analysis of soil in the field. In "Advances in Soil Science" (B. A. Stewart, ed.), pp. 1-70. Springer-Verlag, NewYork. Winteringham, F. P. W. (1980). Nitrogen balance and related studies: A global review. In "Soil Nitrogen as Fertilizer or Pollutant." IAEA, Vienna, Austria. Yoshinari, T., Hynes, R., and Knowles, R. (1977). Acetylene inhibition of nitrous oxide reduction and measurement of denitrification and nitrogen fixation in soil. Soil Biol. Biochem.

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11 Soil Microbial Communities and Carbon Flow in Agroecosystems

Kate M. Scow

I. Introduction The importance of the soil carbon (C) cycle is often overlooked in traditional agricultural studies because the primary focus is on the crop, which is not subject to carbon limitations, and on those nutrients such as nitrogen (N) that do limit productivity. The decomposition portion of the carbon cycle, however, governs many agronomic processes that occur below ground and manifest themselves above ground. Microorganisms control the decomposition of C and their activity regulates nutrient cycling in soils. Even though the consequences of their activities can be quite obvious, the presence of most microorganisms is usually taken for granted in cropping systems. In studies of ecosystems, microorganisms are generally considered not as organisms, in an autoecological sense, but as disembodied rates and pools of nutrients. A better mechanistic understanding of many ecosystem processes could be obtained from knowledge of microbial physiology and metabolism, of the factors controlling microbial populations and activities, and of the spatial and temporal distribution of microorganisms. Steady-state levels of organic carbon in soil are governed by both the input of C, primarily as plant products, and the output of C mediated by the activity of decomposers (Fig. 1). A large fraction of photosynthesized carbon flows through the belowground ecosystem (Heal and MacLean, 1975; Coleman et al., 1976) with most of it passing through microorganisms. Carbon cycling in agroecosystems has a significant impact at the global Ecology in Agriculture

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Figure I

Carbon cycling in an agroecosystem (adapted from Nature and Properties of Soils, 11/E by Brady/Weil, 9 1996. Reprinted by permission of Prentice-Hall, Inc., Upper Saddle River, NJ).

scale because agriculture occupies approximately 11% of the land surface area of the earth (Paustian et al., 1995). This review is concerned with carbon flow through soils in agroecosystems and with the relationships between microbial communities and the biogeochemical cycling of carbon. Primarily, the decomposition portion of the carbon cycle is considered. Emphasis is on microbial populations and with only minor consideration of community interactions and the soil food web. Carbon flow is considered first at the individual microbial cell level, then at the scale of the population and community, and finally in the soil environment, at the pore and aggregate scale. Implications of carbon cycling for the sustainability of agroecosystems are discussed as is the potential for managing soil biology and carbon flow.

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In an ecological context, the following concepts will be developed. Microbial autoecology and community ecology affect C flows at the system level. Microbial ecophysiology is an important factor for C flow in regard to production and assimilation and given starvation of soils. Community structure can influence C dynamics. Spatial and temporal factors affect C availability to microorganisms with ramifications for C flow. All this, in turn, affects agricultural productivity and N and C budgets of environmental importance, e.g., global greenhouse gases.

II. Carbon Flow at the Cellular Level Because many important transformations of carbon are governed by microbial activities, it is important to understand such processes as they occur at the level of the individual microbial cell. Although there is tremendous diversity in the metabolic pathways of microorganisms, certain generalizations can be made for the aerobic, heterotrophic organisms that dominate soil communities in upland agricultural systems. Figure 2 is a simplified depiction of the fate of an organic C compound during its metabolism by

Figure 2 Flowof carbon in a bacterial cell.

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a bacterium. This substrate not only provides a source of energy, resulting in the formation of carbon dioxide (respiration), but also a source of carbon, resulting in production of new cells (assimilation). Other potential fates of C are the formation of extracellular polymers and intermediate metabolites that ultimately become associated with soil organic matter. Fixation of carbon dioxide by autotrophic bacteria, such as lithotrophs and phototrophs, and by many organisms via carboxylation reactions also occurs. However, these processes are not considered further because they have little impact on C flow at the ecosystem scale. The following sections provides an overview of each of the major processes and discusses the implications, for agricultural soils, of how microorganisms use carbon. A. Respiration The use by microorganisms of organic C compounds as electron donors usually produces carbon dioxide, regardless of whether the terminal electron acceptor is oxygen (aerobic conditions) or nitrate (oxygen limited). Conversion from organic to inorganic forms of molecules is termed mineralization. Most organisms capable of C respiration possess the tricarboxylic acid cycle (TCA), at least in part, during which carbon dioxide is released in two reaction steps in the cycle (Brock and Madigan, 1991). Carbon dioxide is also released in the decarboxylation of pyruvate to form acetyl CoA before entry into the TCA cycle. Additionally, decarboxylation occurs in gluconeogenesis, the pentose phosphate pathway, and other reactions; however, the majority of carbon dioxide produced by growing cells is associated with the TCA cycle. As conditions become more reduced, such as in fine-textured, wet, a n d / or carbon-amended soils, then less carbon dioxide is produced. During fermentation, far less carbon dioxide is generated than through respiration and the majority of the carbon is excreted as organic compounds (organic acids and alcohols). Predominance of such reducing conditions is usually temporary in agricultural soils, however, and fermentation products, still rich in energy, are readily mineralized as soon as sufficient oxygen is present. Under highly reduced conditions, there is virtually no production of carbon dioxide; instead, processes carried out by methanogenic bacteria result in the generation of methane from the consumption of carbon dioxide as a terminal electron acceptor. With the exception of flooded agroecosystems such as rice, however, such highly reduced conditions are uncommon in agricultural soils. B. Assimilation and the Yield Coefficient A consequence of the growth of any organism is the incorporation of carbon from the environment into cellular tissue. Thus, the other major function of the TCA cycle is the formation of key intermediates for biosyn-

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thesis. Intermediates from the TCA cycle provide the C skeletons for the production of saccharides, amino acids, nucleic acids, and fatty acids. These monomers are then assembled into the polymers that constitute the majority of the dry weight of a microbial cell. Important groups of polymers include the polysaccharides, proteins, DNA, RNA, and lipids. In general, the monomers, which are often associated with cell cytoplasm, are readily degradable in the soil environment. The polymers, many of which are associated with the cell wall and membranes, are more slow to decompose. Among the polymers are highly resistant structures, for example, lignin and tannin, often associated with cell walls and pigments. Major differences are evident between microorganisms and animals in regard to the flow of carbon through the individual. Assimilation efficiency, which is the proportion of ingested carbon that is assimilated into tissues rather than excreted, is helpful for describing how animals relate to the C cycle because it estimates how much carbon passes untransformed through animal biomass. Assimilation efficiency is less useful for describing microorganisms because microbial uptake and assimilation are often equivalent (e.g., efficiency is 100%) (Heal and MacLean, 1975). Large, complex organic molecules are digested by enzymes outside the cell wall and converted into small compounds that are easy for microorganisms to take up. Also, whereas respiration accounts for a small portion of the carbon consumed by animals and plants, it is a major fate of the carbon consumed by microorganisms. Thus, the production efficiency, which is the proportion of a food source that is used to make biomass rather than respired as carbon dioxide (Heal and MacLean, 1975), is useful for analyzing the impact of microorganisms on the C cycle because of the information it provides about the fate of carbon. Production efficiency is synonymous with the concept of yield, a term commonly used in microbiology. There are numerous approaches for calculating yield, including calculations based on mass or percentage C of substrate consumed, number of electrons transferred, or amount of ATP formed in a reaction (Payne, 1970; McCarty, 1971). In this article, yield is defined as gram cells per gram carbon source, which is directly equivalent to P/A. The calculated yield is presumed to be constant in pure cultures of bacteria when organisms are cultivated in standardized liquid medium under constant conditions (Payne, 1970). The value of the yield coefficient is dependent on the organism but, more important on the particular substrate and electron acceptor used. Yields of many bacteria in pure culture are approximately 60% (Payne, 1970) when growing on simple organic compounds such as sugars and amino acids. From these earlier studies, the widespread use of a yield factor of 50-60% has been adopted as a rule of thumb in many microbiological studies. However, growth on methane or long-chained hydrocarbons results in lower yields, on the order of 25%

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(Payne, 1970). Yields of aerobic growth on a variety of substrates ranged from 12 to 60% depending on the compound and bacterium involved (McCarty, 1971, 1988). Yields of fungi are usually assumed higher than those of bacteria (Alexander, 1977); however, limited data are available even for common soil fungi. Yield varies as a function of various factors. Microorganisms using electron acceptors other than oxygen (e.g., sulfate or carbon dioxide) or obtaining energy from fermentation have yields that are quite low, in the range from 4 to 20% (McCarty, 1971, 1988). Exceptions are organisms using nitrate as an electron acceptor (denitrifiers) that have yields equivalent to organisms using oxygen (McCarty, 1971, 1988). Yields for lithoautotrophs, organisms that obtain their electrons from inorganic molecules, are dependent on the reduction potential of the redox pair that serves as the electron donor. Consistency in cultural and environmental conditions is not an attribute of nature and this makes generalizations about yields more difficult for soil than for pure cultures. Yields of approximately 60% have been observed in mixed cultures of soil and sewage bacteria on pure chemicals as well as on more complex substrates (Payne, 1970). However, in soil studiesJenkinson and Powlson (1976b) and Shields et al. (1974) reported yield values on the order of 40-60% on simple sugars; Heal and MacLean (1975) reported yields ranging from 35 to 60% for mixed populations growing on relatively simple substrates; and Sparling et al. (1981) found values ranging from 8 to 84%. In mixed cultures of microorganisms, one may expect variation in yield for the same substrate under identical growth conditions because of variations in the structure of the microbial community involved in metabolism (Gaudy and Gaudy, 1980). Increasing the carbon to nitrogen ratio of the substrate can increase the apparent cell yield (Gaudy and Gaudy, 1980). When nutrients are limiting, the yield may be half of the value measured under nutrient-sufficient conditions (Chesbro et al., 1979). Yield can be reduced by accumulation of polymers, dissipation of heat by ATPase mechanisms, the presence of inhibitors, or unbalanced ionic concentrations (McCarty, 1971). These stresses, many of which are commonly encountered by soil populations, probably increase the amount of energy used for maintenance rather than growth, thus causing a decrease in yield. C. Maintenance

A portion of the C respired a s C O 2 is associated with expenditure of energy to maintain existing microbial cells. The importance of maintenance is obvious in organisms such as animals that may spend a large portion of their life span not actively growing. Because of the rapid growth rates of microorganisms, and the false assumption that microbial populations must

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grow to be active, maintenance is usually overlooked in microorganisms. Maintenance costs may be trivial for organisms growing in rich laboratory media and in short-term microbiological studies; however, as will be discussed below, these costs may consume a large portion of an organism's substrate under the carbon-starved conditions common to soils. Maintenance C is the C used for purposes other than production of new cell material (Pirt, 1965). Because consumption of C for maintenance results in generation of energy--for osmotic regulation, maintenance of pH gradients, and motility--its ultimate fate is carbon dioxide. Carbon for maintenance may come from a substrate being metabolized or, under starvation conditions, from C stored in reserved cell material (see below). Maintenance has been defined in numerous ways, resulting in some debate; various approaches are well described by Smith et al. (1986). Most considerations of C cycling in soil use the original formulation of Marr et al. (1963) wherein the equation representing the growth rate is modified by addition of a maintenance cofficient that is multiplied by population: ( d S / dt) Y = ( d x / dt) + ax,

where S is substrate concentration, Y is yield, x is the population size, and a is the maintenance rate per cell. Evolution of carbon dioxide is commonly used to measure C flux, in which case the change in the amount of product (e.g., carbon dioxide), corrected for maintenance (Pirt, 1975; Smith et al., 1986), is d P / dt -

Y(p/x) ( d x / d t )

+ ax,

where P is product concentration and Y(p/x)is the yield of product per unit biomass formed. As mentioned previously, discrepancies in the yield term, often seen when comparing different substrate concentrations, may be due to a higher portion of the substrate C being diverted for maintenance energy that would be manifested as a lower apparent yield (Pirt, 1965, 1975, 1982). Consideration of maintenance is hardly a trivial issue in the study of C flow in agricultural soils. Soil populations are usually starved for carbon (Sparling et al, 1981; Behara and Wagner, 1974; Anderson and Domsch, 1978; Jenkinson and Powlson, 1976a). Attempts to calculate generation times or turnover times of the soil microbial biomass have shown that annual C inputs to soil are less than the amount required to support the measured levels of microbial biomass and their hypothetical maintenance requirements, let alone to support increases in the biomass (Smith and Paul, 1990). One of the problems with the analyses described previously is uncertainty regarding the magnitude of the maintenance coefficient (a as defined previously). Maintenance coefficients determined for laboratory cultures

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of bacteria were too high for soil populations, probably because laboratory cultures had not adapted to long-term exposures to nutrient deprivation (Anderson and Domsch, 1985). Arthrobacter globiformas, a soil bacterium, was found to decrease its maintenance coefficient substantially when starved for C (Chapman and Gray, 1981). Maintenance coefficients for soil microbial populations, assuming no net growth, were calculated based on data describing substrate consumption and steady-state biomass levels. The values ranged from 0.001 to 0.003 per hectare (Babiuk and Paul, 1970; Shields et al., 1973; Behera and Wagner, 1974; Paul and Voroney, 1980), approximately an order of magnitude lower than values measured for laboratory cultures. Low maintenance demands of soil microorganisms are presumed to help organisms endure the oligotrophic conditions of soil (Dawes, 1985). Smith and Paul (1989) and Smith (1989) estimated yearly requirements for microbial maintenance in soil based on estimated C inputs and biomass values in various ecosystems. Even assuming the lowest maintenance value reported for soil microorganisms (0.001 per hectare), maintenance demands still far exceeded annual C inputs for almost every system. Smith et al. (1986) proposed a model that includes an active and dormant microbial biomass, cryptic growth, and recycling of dead biomass. In a sensitivity analysis for individual parameters in his model, Smith (1989) found that calculated maintenance rates were most sensitive to total biomass and yield and insensitive to the ratio of the active to dormant biomass and the death rate. When the model was used to calculate maintenance for three ecosystems, and these values were compared to C inputs, inputs were found to exceed maintenance requirements such that microbial biomass could turn over up to eight times annually in a wheat cropping system (Smith, 1989). The calculated maintenance values were approximately 25-50% of the 0.001 per hectare value commonly used for maintenance (Smith, 1989). Although the estimates of maintenance improved in being more compatible with measured data, Smith (1989) concluded the estimates were still flawed by lack of consideration of temporal fluctuations in both C inputs and microbial physiology, both of which were represented by average annual values in the model. D. Other Metabolic Products

Organisms not limited by carbon can undergo uncoupled growth, due to lack of other required nutrients, resulting in energy-spilling reactions that result in the synthesis of storage polymers and excretion of extracellular polymeric substances (Dawes, 1985). Storage compounds in microorganisms include carbohydrates (polyglucans, and glycogen), lipids (poly-flhydroxybutyrate and polyalkanoates), polyphosphates, and cyanophycin/ phycocyanin (Dawes, 1985). Poly-/3-hydroxybutyrate may also serve as an electron sink for excess reducing power when cells become oxygen limited

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and activity of the electron transport chain ceases (Dawes, 1985). Accumulation of storage compounds appears to enhance survival of microbial isolates under starvation conditions. Other common products of microbial synthesis are alkyl C compounds such as polymethylene (Kinchesh et al., 1995; Baldock et al., 1990). Many of the extracellular polymeric substances are polysaccharides containing common sugars (e.g., glucose, galactose, and mannose), uronic acids, pyruvate and N-acetylated amino sugars (e.g., glucosamine and galactosamine), as well as smaller amounts of more unusual sugars (Christensen, 1989). Most are hydrophilic and have zero or net negative charge. Both bacteria and fungi produce these substances. Examples of specific types of polysaccharides include cellulose, dextran, alginate, xanthan, scleroglucan, and gellan (Kenne and Lindberg, 1983). At high C input rates, especially when nitrogen or other nutrients are limiting, a considerable amount of substrate C may be converted to extracellular metabolites (Sparling et al., 1981). E. Implications of the Metabolic Fate of C for Soil Processes What occurs at the level of the microbial cell has enormous impacts at the scale of the agroecosystem. Figure 3 summarizes potential interactions between the products of microbial metabolism and the soil. The most striking result of heterotrophic microbial metabolism is the loss of carbon from soil. It is common that from 40 to 60% of the C taken up by microorganisms is immediately released as carbon dioxide during metabolism. Higher microbial yields would therefore be desirable if the objective is to accumulate C in soil. Assimilation has implications beyond simply the retention of C in microbial tissue. Not all compounds created by microorganisms are rapidly degraded. Cell wall components, being polymers, are less biodegradable than cytoplasm constituents. Some fungal cell walls, in particular, are highly resistant to breakdown because they are composed of polysaccharidemelanin complexes or of heteropolysaccharides (Martin and Haider, 1979; Alexander, 1977). For example, in soil, radiolabeled cell wall material from the fungus Aspergillis degraded more slowly than cell walls of the bacterium Azotobacter (Mayaudon and Simonart, 1963). Labeled melanins extracted from two fungal species were mineralized less than 10% in 3 months (Martin and Haider, 1979), which is far less than amounts mineralized from plant residues in the same time. Fungi and actinomycetes can directly produce humic-like material very similar to humus extracted from soil (Martin and Haider, 1971; Huntjens, 1972). Also important to C flow is the physical location of microbial-produced substances and microorganisms in the soil matrix. Using electron microscopy, Foster (1981) found that soil extracellular polymers are most often

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Figure 3 Role of microbial processes in the flow of carbon through soil.

associated with the clay fraction. Polysaccharides are protected from decomposition through their interaction with clay, metal ions, and tannins (Tisdall and Oades, 1982). Intact bacterial colonies and fungal hyphae in soil are commonly coated with fine clay, C of microbial origin is often extracted in the clay fraction of soil, and microbial-mineral associations are important in the formation of soil aggregates (Tisdall and Oades, 1982). The common association of microbial products (such as alkyl C compounds) with clay increases their resistance to mineralization (Guggenberger et al., 1995; Kinchesh et al., 1995). Interactions between microorganisms and the soil matrix are discussed in greater detail in a later section.

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III. Carbon Flow: Populations and Communities Although among microorganisms there are some similarities in how individual cells utilize carbon, C flow in soil is also affected by the size of microbial populations and the composition of their communities. Although the entire microbial biomass is usually treated as a single entity, major functional or taxonomic groups can sometimes be distinguished. Few studies concern interactions among functional groups, let alone among individual species, within the microbial community. Potential interactions have strong impacts, at least theoretically, on C flow and include (i) the exchange of transformed carbon compounds, often resulting in more efficient utilization of the potential energy present in organic material; (ii) the exchange of other chemical compounds, such as electron acceptors or nutrients; (iii) competition for C and other nutrients; and (iv) predation and parasitism, which lead to the introduction of C into the food web. The following sections will briefly consider C flow as it is related to the microbial biomass, to differences between bacteria and fungi, and to the soil food web. A. Microbial Biomass

Given the enormous diversity of microorganisms in soil, it is not practical or even feasible to consider differences in C flow among species. Both the structure (e.g., community diversity and species distribution) and function (e.g., process rates) are important in characterizing ecosystems, but it has long been assumed in ecology that the latter becomes more important as the size of organism decreases (Odum, 1971). There have been serious methodological limitations in our ability to characterize microbial communities, although recently there have been major advances (Ritz et al., 1994). New methods include extracting microbial cellular material, such as phospholipid fatty acids or DNA, directly from soil and using this information for estimating overall diversity or identifying taxonomic groups (Tunlid and White, 1992; Zelles et al., 1992; Torsvik et al., 1994). In studies of C flow, it is common to ignore species diversity and, at least implicitly, assume the total microbial biomass functions as a supraorganism, as represented as a single compartment in many C flow models (e.g., Jenkinson and Rayner, 1977). Similarly, flows between pools of C, largely controlled by microorganisms, are represented by single rate constants that reflect the collective activity of many species. Substantial research over the past two decades has focused on the microbial biomass in soil (Smith et al., 1993; Lynch and Panting, 1982; Paul and Voroney, 1980; Smith and Paul, 1989). Numerous methods have been developed to measure the soil microbial biomass, including the chloroform fumigation incubation method, the chloroform fumigation extraction

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method, substrate-induced respiration, and adenosine triphosphate analysis (Horwath and Paul, 1994). Microbial biomass varies significantly among soil types and vegetation systems. Values for biomass range from 30 to 2780/~g C per gram of soil (Bolton et al., 1985). The C contained in microbial biomass ranges from 0.5 to 5% of the total organic C in the soil (Jenkinson and Ladd, 1981; Marumoto et al., 1982). Being one of the most labile pools of soil organic matter, microbial biomass is an important reservoir of plant nutrients (Marumoto et al., 1982; Jenkinson and Ladd, 1981; Smith and Paul, 1986), as will be discussed in a later section. Because process rates are strongly dependent on the size of microbial populations, quantification of total microbial populations is important in estimating the rates at C turnover. However, microbial biomass is too gross a measure to be useful for most specific processes and better progress can be made in quantifying specific groups using most probable number methods (Woomer, 1994), immunofluorescent direct counts (Bottomley, 1994), or biomass estimation in conjunction with specific inhibitors (Anderson and Domsch, 1973). Another important issue in linking microbial populations to carbon flow is distinguishing between the dormant and active microbial biomass (Smith et al., 1993). Smith etal. (1986, 1993) distinguish between the active portion of the microbial population, which grows, and a sustaining population, which has only maintenance demands. This distinction is important for estimating turnover times of microbial biomass, where the turnover times of the total biomass range from 2 to 6 years and that of the active biomass from 0.3 to 1 year (Smith et al., 1986) Microbial biomass is sensitive to perturbation by agronomic practices or other factors (Smith and Paul, 1986; Doran, 1987). The size of the soil microbial biomass is related to the mass of C and other nutrients available from plant residues and root exudates (Fraser et al., 1988; Adams and McLaughlin, 1981) and is strongly influenced by rainfall or irrigation (Campbell and Biederbeck, 1976). Microbial biomass is also positively correlated to an estimate of the organic nitrogen available to crops in no-tillage surface soil (Doran, 1987). The magnitude of microbial biomass depends on environmental conditions (e.g., rainfall) as well as degree of disturbance or age of an ecosystem (Insam et al., 1989). It has been proposed that the ratio of microbial biomass carbon to total organic carbon (Cmic/Corg)reflects the "stability" of the organic matter content of an agricultural ecosystem (Anderson and Domsch, 1986, 1989); this hypothesis remains to be tested with long-term studies.

B. Composition of Microbial Communities: Bacteria and Fungi Differences in microbial community composition may directly affect carbon flow. For example, the low mineralization potential of an occluded, labile organic matter pool in a no-fill soil was attributed to its origin as

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fungal cellular material (Cambardella and Elliot, 1994). Many assumptions about the microbiology of C dynamics in soil are biased by the fact that bacterial processes are better understood than fungal processes. Soil fungi, however, often constitute a greater portion of the total soil biomass than do bacteria. Forest litter and soils, for example, are largely dominated by fungi (Cromack and Caldwell, 1992). Shields et al. (1973) and Nannipieri et al. (1978) found, using direct counting techniques, that bacteria comprised only 15-20% of the biomass in agricultural and grassland soils. Chemical inhibitors that selectively interfere with 70 S- or 80 S-type ribosomes are often used to separate eukaryotes from prokaryotes. Using such inhibitors, Anderson and Domsch (1973, 1980) also estimated that fungi contributed 60-90% of the total short-term respiration in 14 arable soils. The ratio of prokaryotic to eukaryotic biomass was 1 : 4 in two agricultural soils and 1:9 in a forest soil (Anderson and Domsch, 1978). However, not all agricultural systems are dominated by fungi. Bacteria are more abundant than fungi in arable reclaimed marine sediments in The Netherlands (Moore and de Ruiter, 1991) and in Colorado soils cultivated with spring wheat (Holland and Coleman, 1987). Abundances of particular predatory groups, e.g., bacterial versus fungal feeding nematodes, may reflect differences in the proportions of bacteria and fungi (Moore and de Ruiter, 1991). Composition and management of plant residues are important determinants of the relative importance of fungi and bacteria. Among cellulolytic microorganisms, fungi tend to be selected for by plant residues with high C / N ratios, whereas bacteria tend to be selected by lower C / N ratio material (Broder and Wagner, 1988). Fungi had a greater influence on decomposition in no-fill systems in which surface residues select for organisms that can withstand low water potentials and obtain nutrients from the underlying soil profile (Beare et al., 1992). Bacteria were more important in tilled soils where residues were well mixed into the soil profile. There are also a number of important physiological and ecological differences between bacteria and fungi. Anderson and Domsch (1980) found large differences in the elemental composition of 24 species of common soil bacteria and fungi. Carbon to nitrogen ratios averaged around 5.5 for the bacteria and 8.3 for the fungi and average C contents (mg per dry weight of cells) were 430 for the bacteria and 373 for the fungi. Fungi conserve more energy than do bacteria and can recycle nutrients internally by translocating cytoplasm. Within the fungal biomass, levels of N vary considerably. Paustian and Schn(irer (1987) found levels of N to be 1 or 2% (dry weight) in cell walls and 10% in the cytoplasm of fungi. Fungi often produce proportionally more cell wall than cytoplasmic material when starved for N and thus can extend into new regions of the soil without requiring balanced growth conditions. Filamentous fungi can grow more effectively than bacteria under conditions of low moisture and low pH

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(Beare et al., 1992; Holland and Coleman, 1987). Because bacteria are smaller than fungi, they can occupy smaller pores and thus potentially have greater access to material contained within these pores. Although neither group of organism is very mobile in soil, the filamentous growth structure of a fungus permits it to access C in one location, e.g., on the surface, and nutrients in another location, e.g., in the soil profile (Holland and Coleman, 1987). Degree of disturbance associated with cultivation is inversely related to fungal biomass (Hunt et al., 1989). Fungi are also more disrupted than are bacteria by the tillage practices commonly used in agriculture (Johnson and Pfleger, 1992). Many conclusions about the importance or lack of importance of fungi in agricultural soils are based on laboratory studies using very disturbed soils. Therefore, the importance of fungi in agricultural soils may be underestimated (Moorhead and Reynolds, 1992). The bacterial species composition of soil communities is also important to C cycling, although methodological limitations have previously hindered studies that consider diversity and community structure. Cycling of nutrients can be dependent on close relationships among various trophic groups. For example, C flow in anaerobic systems is dependent on close spatial and temporal interactions and exchange of C sources and electron donors among different functional groups of bacteria (Brock and Madigan, 1991). These groups include fermenters, hydrogen-producing acetogenic bacteria, and sulfate-reducing bacteria and methanogens. Similarly, an aerobic community in close proximity to an anaerobic community will metabolize and assimilate reduced substances (e.g., methane) and thus conserve C within the system. Whether greater species diversity within functional groups can influence C dynamics is not yet known. Recent developments in the application of phospholipid fatty acid (PLFA) and molecular analysis to whole communities are rapidly improving our capabilities to consider microbial diversity and community structure in soils (Ritz et al., 1994). Both approaches utilize microbial cellular material, directly extracted from soil, to provide information about the composition and metabolic status of soil communities. Phospholipids are integral components of cell membranes and are rapidly metabolized when a cell dies in soil; therefore, they provide an accurate measurement of living biomass (White et al., 1979). Principle types of fatty acids are defined on the basis of chain length, degree of unsaturation, and the presence of substituents (e.g., methyls, hydroxyls, and cylopropane rings). Whereas bacterial fatty acids usually range from C-12 to C-20 and include odd-chain, methylbranched, and cyclopropane fatty acids, fungal fatty acids are typically longer in length and contain saturated even-chain and polyenoic fatty acids (Tunlid and White, 1992). The entire PLFA profile can be used as a

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"fingerprint" of the whole soil community. Also, specific signature lipids are used to discriminate among different microbial taxonomic groups. Microbial community structure in agricultural ecosystems has been characterized based on phospholipids (Bossio and Scow, 1997; Zelles et al., 1992, 1995). PLFA profiles were measured in soil microbial communities from organic (amended with cover crops and manure), low-input (cover crops and mineral fertilizer), and conventional (mineral fertilizer) farming systems of the Sustainable Agriculture Farming System Project in California (Temple et al., 1994; Gunapala and Scow, 1997). Sustained increases in microbial biomass and activity, resulting presumably from high organic matter inputs, had been previously observed in the organic and low-input tomato soils (Gunapala and Scow, 1997). PLFA profiles of the communities in organic and conventional soils were significantly different throughout the growing season based on multivariate statistical tests. The low-input profiles fell intermediate between the organic and conventional soils on most sample dates. The organic and low-input soils had higher ratios of fungal to bacterial signature PLFAs than did the conventional soil. Diversity indices, using PLFAs as "species," were the same in all farming systems and across all dates. Changes in PLFA profiles over the season were larger than changes associated with farming system practices, except immediately following cover crop or fertilizer amendment. Spatial variation in PLFA profiles across field blocks was relatively insignificant. Comparison of the PLFA profile from the SAFS tomato soils with soils cultivated with rice showed that the differences between the two soil types were far greater than any differences within soil type associated with farming system and seasonal variations (Bossio and Scow, 1997). PLFA analysis thus proved to be a promising approach for relating microbial community composition to agricultural practices. C. Soil Food Web

Microorganisms are members of complex soil food webs that also include numerous species of protozoa, arthropods, oligochaetes, annelids, molluscs, and other organisms (Killham, 1994). These micro- and macrofaunal species are important as predators of bacteria and fungi, as well as processors and mixers of newly added organic material in soil. Food webs have been described by (i) "connectedness" web models that emphasize the diets and trophic relationships among groups of organisms (common in studies of communities); (ii) energy flow models that estimate the fluxes of material (e.g., C as the carrier for energy) through different groups (common in studies of ecosystems); and (iii) functional web models that address biological interactions that determine the size and activity of functional groups (often integrate aspects of i and ii) (Paine, 1980; Moore and de Ruiter, 1991). Energy flow models tend to be biased toward, and most sensitive

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to, organisms with high biomass and turnover rates (e.g., microorganisms). Higher trophic levels may seem insignificant in such models if one considers the small portion of material, energy or elemental, that flows through their biomass. The regulation and stimulation of microbial populations by the higher trophic levels, however, can significantly affect C flow (Moore and de Ruiter, 1991; de Ruiter et al., 1995). For example, the removal of mites from plots in the Chihuahuan desert resulted in larger populations of bacterial-feeding nematodes, reduction in bacterial populations, and reduction in rates of decomposition of desert shrub litter (Santos et al., 1981). The presence of nematodes can increase the fraction of C that is respired by microorganisms (Ingham et al., 1985). Through their predation on bacteria, protozoa can substantially increase the mineralization and plant uptake of nitrogen in soil (Clarholm, 1994; Kuikman et al., 1990).

IV. Carbon Flow at the Soil Level The majority of C enters the soil in the form of complex organic matter containing highly reduced, polymeric substances. During decomposition, energy is obtained from oxidation of C - H bonds in the organic material. When oxygen becomes limiting, many inorganic compounds are reduced during their use by bacteria as electron acceptors. When decomposition slows down, oxygen again becomes available, and the reduced inorganic compounds are reoxidized because they provide electron donors and reducing equivalents for chemolithotrophic microorganisms. These oxidations and reductions are the reactions underpinning the biogeochemical cycles of C, as well as nitrogen, sulfur, and other elements, that are essential to the functioning of agroecosystems. A. Inputs of C to Soil

Plants are the major sources of C to soil in agroecosystems. Cropassociated C enters in the form of litter, stubble, roots, and root exudates. Organic amendments, such as cover crops, compost, and manures, are other important sources of C. Although organic pesticides are a potential source of C, they contribute a very small amount of C, usually on the order of < 0.001% of the total organic C in soil. Distinguishing between types of organic inputs, even within a plant, is important because of differences in the time and frequency of their addition to soil, as well as in their chemical composition. Although quantification of the aboveground biomass is relatively simple, estimating total C inputs from plants is complicated by uncertainties about the true root biomass and about losses due to plant respiration, grazing, and death. Shoot to root ratios (not accounting for losses from roots) for temperate, herbaceous

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plants, including cultivated crops, ranged between 1.2 and 1.5 (Buyanovsky and Wagner, 1986). Significantly higher ratios, ranging from 2 to 5, have also been reported for cultivated crops (Beauchamp and Voroney, 1993). Perennial crops rarely enter the reproductive phase because of frequent cutting, and thus allocate more of their total productivity below round than do annual crops. The shoot to root ratio mayvary with fertilization (Hansson et al., 1990) and growth stage (Keith et al., 1986). Amounts of C associated with crop residues incorporated into the soil depend on the particular crop and vary widely (Smith et al., 1993). For example, the estimated C inputs to soil with postharvest residue of wheat and soybean were 343-372 g / m 2, whereas inputs following corn harvest were almost three times higher (Buyanovsky and Wagner, 1986). Root exudates, including sloughing of root cells, can account for 10-33% of the net plant photosynthate (Beauchamp and Voroney, 1993). Bowen and Rovira (1991) estimated that total exudation and grazing loss by soil predators may account for as much as 150% of C in the root biomass at harvest. The temporal and spatial distribution of inputs can vary substantially. Root exudates enter the soil throughout the growing season, whereas the residue from crops, as stubble and root mass, enters the soil in a pulse following harvest. Spatial distribution of the root biomass depends on the crop; approximately 76, 64, and 79% of the total root biomass of wheat, soybean, and corn, respectively, was in the top 10 cm of soil at harvest (Buyanovsky and Wagner, 1986). Incorporation of cover crops and manures occurs in a single pulse, in spring, before planting. Distribution of these inputs is in the top 10-15 cm of soil, if filled, or on the soil surface in notill systems (Beare et al., 1992). B. Pools o f Carbon within Soil

Soil organic matter (SOM) has been the subject of numerous recent reviews and books (Stevenson, 1994; Coleman et al., 1989; Chen and Avimeb ech, 1986; MacCarthy et al., 1990; Wilson, 1991) and will only briefly be considered 'here. SOM consists of a broad spectrum of chemical classes, including (but not limited to) amino acids, lignin, polysaccharides, proteins, cutins, chitins, melanins, suberins, and paraffinic macromolecules, as well as anthropogenic chemicals. A major organic fraction, associated with mineral surfaces, is collectively known as humic material, which consists of amorphous macromolecules derived from the preceding list of biogenic precursors (Hayes, 1991). There is no consensus on the exact structure of humic material in soil, though a number of hypotheses have been proposed (Stevenson, 1994; Schnitzer and Khan, 1978; Hayes, 1985). The pools of organic matter in soil have been characterized by numerous approaches, including chemical fractionation, physical fractionation, and

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biological methods (Stevenson, 1994; Stevenson and Elliot, 1989). Although the pools defined are often not equivalent across methods, the use of multiple approaches has increased our understanding of C dynamics in soil. Organic matter fractions obtained by chemical methods are operationally defined and may be artifacts or products of harsh extraction methods (Stevenson and Elliot, 1989). Chemically fractionated SOM is usually divided into nonhumic substances, such as carbohydrates, lipids, and proteins, and humic substances, such as humic acid, fulvic acid, and humin (Stevenson, 1994). The humic substances are highly complex and not well characterized. Humin may consist of tightly bound and condensed humic material, fungal melanins, and paraffinic molecules (Stevenson and Elliot, 1989). It has proven difficult to relate amounts and structures of humic substances to their function or behavior in soil. New approaches in analytical chemistry have improved our ability to analyze chemical fractions extracted from soil. Nuclear magnetic resonance (NMR) spectroscopic techniques are now used to study humic substances (Malcolm and McCarthy, 1991). Analytical pyrolysis (py) is used to study soil organic matter via gas chromatography-mass spectrometry (pyGC-MS) and py-direct mass spectrometry (Haider and Schulten, 1985; Schnitzer and Schulten, 1992). pyGC-MS can be used to analyze whole soils and does not require extraction of humic substances. Emerging methods for characterizing soil C pools are aimed at maintaining the interrelationships between organic and mineral components. Combinations of these methods have been more fruitful than chemical approaches alone in investigations of C flow in soils. Figure 4 shows a flowchart of the physical fractionation approach (Stevenson and Elliot, 1989). Physical fractionation techniques include separation by sieving (usually particles and aggregates >50/.r sedimentation (particle sizes >2/zm), and densitometry. Studies using different fractionation methods are often difficult to compare because of differences in soil preparation, size fractions, and reagents used in density separation. Various methods for sieving and sedimentation of soil are described by Stevenson and Elliot (1989) and Christensen (1992). These approaches separate out soil fractions by diameter or size, shape, and density. Following separation, the organic matter associated with each fraction may be quantified as total C, analyzed for specific chemical constituents, incubated to determine the bioavailability of its C, or carbon dated (Stevenson and Elliot, 1989; Anderson and Paul, 1984). Studies of the C associated with particles and aggregates are discussed in a later section. Care must be taken in making generalizations about C flow because excessive sonication can fragment the soil and generate new material within size fractions. In addition, the nonideality of soil particles may violate Stoke's law, generating uncertainty

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tant for examining the direct C O 2 effects and climate change separately. The different concentrations in the scenarios led to different temperature changes. The baseline-A led to an increase in temperature of 2.5~ at 2.5 times the current CO2 level by 2100. The more stringent scenarios limited the temperature change to I~ by 2100. Initially, all scenarios followed a

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similar pattern and the difference in efficiency of these policy measures became apparent only after 2025. This also implies the impacts were similar in these early stages. Only after 2025 did the different scenarios strongly vary. There was one clear difference among the scenarios. In three scenarios, the LESS-BI, St2000 Glob ALL-1% and Stab 450 ALL, the impact levels stabilized, whereas for the other scenarios they continuously increased. The impact levels for temperate cereals (C3 species) were generally lower than those for maize (a C4 species). This was caused by differences in CO2 fertilization for these species, which offsets the negative impacts of climate change. C3 plants are responsive to higher CO2 levels, whereas C4 plants are not. This finding is similar to those in the earlier studies. Also, shifts in potential vegetation were clearly different among the scenarios. These scenario studies show that this type of integrated model is capable of simulating many components of the earth's system comprehensively. Policy options to mitigate the buildup of GHGs can be tested and their consequences for other possible options evaluated. Optimal response strategies can be developed in this way. The LESS-BI scenario is a good example of this. IMAGE 2 also has the capacity to address other environmental issues, such as food security and biodiversity. Impacts on biodiversity are, for example, a clear function of changes in potential vegetation and land use. Within IGBP, IMAGE 2 is currently used to develop scenarios for biodiversity change (Steffen et al., 1996).

V. Concluding Remarks In this chapter, the different approaches to impact assessments of climate change on agricultural and ecological systems have been discussed. Such impacts should not be treated in isolation from other components of the climate-biosphere-societal system. Many different models have been developed, environmental data sets have been compiled, and experiments have been conducted to increase our understanding of the local physiological and ecological processes. This understanding is relatively high, especially if we treat processes individually. However, the interaction between processes and factors influencing them has been neglected until recently. The importance of agricultural and ecological research on such interactions and under realistic conditions cannot be stressed enough. Furthermore, the linkages with socioeconomic research and understanding are needed to assess the actual responses to climate change. In this field of research we are only starting to enhance our knowledge ( Turner et al., 1995). Integrated approaches and IAMs can highlight gaps or incompatibilities between disciplines a n d / o r scientific understanding. These methods have not only relevance as a policy tool: Scientifically speaking, they are objective

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tools to emphasize the systemic and highly nonlinear linkages between the different components of the earth's system. The research activities of the major international programs (SCOPE, WCRP, IGBP, and IHDP) will advance the development of these approaches. Linkage with remotely sensed data, for example, can assist in obtaining the geographic coverage needed. Data dissemination centers, such as CIESIN and CDIAC, and connections through the Internet provide a necessary link to standardizing some of the input data sets. Model comparisons, such as VEMAP by Melillo et al. (1995), will further highlight discrepancies in our understanding and guide both modeling and experimental research. Scientifically speaking, this is an exciting era, in which large-scale global environmental change is pushing the advancement of both basic and applied research on smaller scales. It is necessary to integrate the knowledge from cell to leaf to plant to plot to ecosystem, and on to region and the world. The relatively small-scale physiological and ecological processes in the biosphere play an important role in this respect. Despite the complexity of the earth's system, major achievements in combining disciplinary expertise from many different natural and physical sciences have been rapid during the past few years. However, the largest challenge is still to come. These scientific achievements need to be integrated with the expertise of the social, cultural, and economic sciences. Particularly important is the development of adequate policies for global environmental change in which sustainable use of natural resources to accommodate an increasing human population is allowed for; this demands a better understanding of the interactions between the environment and human behavior. Scientists' major challenge is probably to guide policy makers and leaders to appropriate ways for reducing the threats of global environmental change.

Vl. Summary The small-scale physiological processes on plant and ecosystem levels and the environmental constraints of these processes determine the distribution and yields of crops and ecosystems. Plants, fields, and ecosystems define the fluxes of C, N, water, and energy between the biosphere and atmosphere and thus form an important component of the earth's system. Interaction and feedback between atmospheric changes and the biosphere determine the consequences of global environmental change. This chapter discussed different modeling frameworks to assess such consequences at different levels. It is stressed that most disciplinary models, i.e., those that only simulate a component without considering changes in or influences from other components, can lead to misleading results, especially when they are

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linked to environmental change scenarios of limited quality. Integrated assessment models were described in this chapter. These models link societal developments with the biosphere and other components of the earth's system. Only comprehensive models such as these can bridge the gaps between (i) use of our best scientific understanding of small-scale physiological and ecological processes, of local, regional, and global scales, and of the interactions between different components of the earth's system; and (ii) meeting the requirements of policy advisors and those of policy makers for developing consistent policy measures and strategies to address global environmental change.

VII. Appendix Direct Effects o f Increased CO2 Concentrations on Plant Growth

Plants fix CO2 during photosynthesis. This process takes place in all green plant cells. Three very different photosynthesis pathways are distinguished: C~, C4, and CAM. The pathways differ in their first carbon organic acid of the photosynthesis process ( a three-carbon compound, a four-carbon compound, and crassulacean acid, respectively). These pathways have evolved under specific environmental conditions and can be recognized by different leaf morphologies and physiologies. C~ plants are globally the most common. They include all important tree and most crop species, such as wheat, rice, and potato. Their complete photosynthesis occurs in single cells immediately under the epidermis of a leaf and the photosynthesis reaction is reversible and therefore less effective (see Chapter 2, this volume). This results in higher photosynthesis rates at higher ambient CO2 concentrations. This is the so-called CO2 fertilization effect. Annual plants tend to be more responsive t o C O 2 than perennial plants and herbaceous more than woody plants. The responses are species specific. C4 plants tend to grow in warmer, more water-limited regions and include many tropical grasses and the agriculturally important species corn, sugarcane, and sorghum. C4 plants initially fix CO2 in specialized cells near the epidermis of the leaf. This fixed C is transported as a C4 compound to inner cells where the final photosynthesis occurs. This mechanism concentrates internal C levels and this results in an efficient photosynthesis. This pathway is much less responsive to changes in ambient CO2 concentration. It has been suggested that this pathway evolved in an era with low CO2 concentrations. The CAM pathway involves plants, such as cacti, adapted to extreme droughts. It is a variant of the Ca pathway. The difference, however, is that the CO2 is not only transported internally but also stored as crassulacean

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acid. In these plants C O 2 uptake occurs at night to reduce water losses during the day. An important effect of changing CO2 levels is also changes in WUE. Ambient CO2 diffuses through stomata into the leaves. Simultaneously, water is lost to the atmosphere. The ratio between C gain and water lost is defined as WUE. U n d e r higher CO2 levels, stomata close and less water is lost, while photosynthesis continues at normal rates. This increases WUE and allows plants to grow u n d e r more arid conditions. Increased WUE occurs in all plant types. This process is probably one of the main causes of long-term adaptation of CO2 fertilization in C~ plants: Plants tend to return to " n o r m a l " photosynthesis rates when grown u n d e r high CO2 levels. Detailed discussions of these processes can be found in Melillo et al. (1996) and Kirschbaum et al. (1996).

Acknowledgments Funding by the Netherlands Ministry of Housing, Spatial Planning and Environment under Contract MAP410 has made this contribution possible. The research on IMAGE 2 was facilitated by funds provided by the National Research Programme on Global Air Pollution and Climate Change and contributes to IGBP-GCTE core research. The author has also received numerous suggestions for this paper from other experts during the development of the Second Assessment Report of IPCC (SAR). Without their comprehensive compilations this chapter would have suffered from many limitations. Specific comments by B. de Vries, G.J. van den Born, R. de Wijs, and an anonymous reviewer on earlier drafts were highly appreciated.

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Rosenzweig, C., and Parry, M. L. (1994). Potential impact of climate change on world food supply. Nature 367, 133-138. Rotmans, J., de Boois, H., and Swart, R.J. (1990). An integrated model for the assessment of the greenhouse effect: The Dutch approach. Climatic Change 16, 331-356. Smith, T. M., Leemans, R., and Shugart, H.H. (1992). Sensitivity of terrestrial carbon storage to CO2 induced climate change: Comparison of four scenarios based on general circulation models. Climatic Change 21,367-384. Smith, T. M., Leemans, R., and Shugart, H. H. (eds.) (1994). "The Application of Patch Models of Vegetation Dynamics to Global Change Issues." Kluwer, Dordrecht. Solomon, A. M. (1986). Transient responses of forests to CO2-induced climate change: Simulation modeling in eastern North America. Oecologia (Berlin) 68, 567-579. Solomon, A. M., Prentice, I. C., Leemans, R., and Cramer, W.P. (1993). The interaction of climate and land use in future terrestrial carbon storage and release. Water Air Soil PoUut. 70, 595-614. Steffen, W. L., Chapin, F. S., and Sala, O. E. (1996). Global change and ecological complexity: An international research agenda. Tr. Ecol. Evol. 11, 186. Turner, B. L., II, Clark, W. C., Kates, R. W., Richards, J. F., Mathews, J. T., and Meyer, W.B. (eds.) (1990a ). "The Earth as Transformed by Human Action: Global and Regional Changes in the Biosphere over the Past 300 Years." Cambridge Univ. Press, Cambridge, UK. Turner, B. L., II, Kasperson, R. E., Meyer, W. B., Dow, K. M., Golding, D., Kasperson, J. X., Mitchell, R. C., and Ratick, S.J. (1990b). Two types of global environmental change: Definitional and spatial-scale issues in their human dimensions. Global Environ. Change 1, 14-22. Turner, B. L., Skole, D. L., Sanderson, S., Fischer, G., Fresco, L., and Leemans, R. (1995). "Land Use and Land-cover Change: Science/Research Plan," IGBP Rep., November 1995. IGBP, Stockholm. van Minnen, J. G., Klein Goldewijk, C. G. M., Leemans, R., and Kreileman, G. J.J. (1996a). "Documentation of a Geographically Explicit Dynamic Carbon Cycle Model," RIVM Rep., January 1996. Bilthoven. van Minnen,J. G., Klein Goldewijk, IC, and Leemans, R. (1996b). The importance of feedback processes and vegetation transition in the terrestrial carbon cycle. J. Biogeogr. 22, 805-814. Viner, D., Hulme, M., and Raper, S.C.B. (1995). Climate change scenarios for the assessments of the climate change on regional ecosystems. J. Therm. Biol. 20, 175-190. Vitousek, P. M., Ehrlich, P. R., Ehrlich, A. H., and Matson, P.A. (1986). Human appropriation of the products of photosynthesis. BioScience 36, 368-373. Watson, R. T., Zinyowera, M. C., and Moss, R. H. (eds.) (1996). "Climate Change 1995. Impacts, Adaptations and Mitigation of Climate Change: Scientific-Technical Analysis." Cambridge Univ. Press, Cambridge, UK. Weyant, J., Davidson, O., Dowlabathi, H., Edmonds, J., Grubb, M., Parson, E. A., Richels, R., Rotmans, J., Shukla, P. R., Tol, R. S.J., Cline, W., and Fankhauser, S. (1996). Integrated assessment of climate change: An overview and comparison of approaches and results. In "Climate Change 1995. Economic and Social Dimensions of Climate Change" (J. P. Bruce, H. Lee and E. F. Haites, eds.), pp. 367-396. Cambridge Univ. Press, Cambridge, UK. Wigley, T. M. L., Richels, R., and Edmonds,J. A. (1996). Economic and environmental choices in the Stabilization of atmospheric CO2 concentrations. Nature 379, 240-243. Zuidema, G., van den Born, G. J., Alcamo, J., and Kreileman, G. J. J. (1994). Simulating changes in global land cover as affected by economic and climatic factors. Water Air Soil Pollut. 76, 163-198.

Index

Abutilon, 297, 316 Acacia, 267 Acclimation, 46-56 Acid growth, in roots, 161 Acidity, in ammonium toxicity, 149 Active transport of ammonium, 146-151 costs, 63, 64, 66 of nitrate, 153-155 Adaptive response program, 29, 48-49 aegilops, 13, 21,314-315 Agave, 187 AGCMS, 426-427, 428, 429, 431 Agricultural selection, 8-12 in host-pathogen coevolution, 207-209 Agriculture, see also Agroecosystems biodiversity, historical presence, 203 effects on habitat, 8, 47-48 genetic erosion in, 222 hybrids in, 49 impacts of global environmental change, 420, 424-433 land loss, 228 selection in, 8-12, 207-209 styles, soil microbial communities and, 381 subsistence, 9-11,223 Agroecosystems competition and interference in, 296 host-pathogen coevolution in, 207-209 interactions with natural ecosystems, 212 island analogy in, 248-250 landscape heterogeneity and, 249, 271, 274 modeling, 418-423 soil carbon flow and, 367-369, 396-397 tree plantings and, 228 Agroforestry, 217 AIM model, 436 Alfalfa, carbohydrate storage, 66

Alkaloids, 256, 257-258 Allelopathy, 296 AUium, 298, 311 Alnus, 306 Alternaria, 211 Amaranthus, 297, 304, 309 Ambrosia, 265, 297 Amblyseius, 263 Ammonia anhydrous, 352 diffusion, 146-148 Ammonium acquisition, 22, 146-151,152-153, 161-162 assimilation, 151-152, 158 membrane depolarization and, 147,. 150-151 movement., in soil, 163 nitrate uptake, inhibition of, 154 in nitrogen cycle, 349 plant growth and reproduction, 158-159 root carbohydrate levels and, 153 root growth and, 159-160 toxicity, 148-149 Amsinckia, 320 Analytical pyrolysis, in soil analysis, 384 Anasa, 265 Angoumois grain moth, 244 Anguina, 320 Angular leaf spot, 220 Animal feed, mixed cropping in, 226 Anion, mobility, 151

Anthemis, 318 Ants, 265 AOS model, 438 Aphid, 246, 251 Apiaceae, chemical defenses in, 257 apion, 250 Apple, root life span in, 193 Arabidopsis, 178 453

454

ln~x

Arachis, 87, 314 Aromatic compounds, in plant defenses, 257 Arrhenatherum, 194 Arthrobacter, 374 Arthropods, phytophagous, see also Plantarthropod interactions attractive plant compounds and, 264-265 categories of, 241 colonizer pools, 248-249 counterresistance and, 251,259 crop exploitation, 242-243 early successional plants and, 243-244 general traits, 242 outbreaks, 240-241,249-250 photosynthesis responses, 61 plant secondary metabolites and, 256-257 predators and parasitoids of, 263-264 wild plants and, 242, 243 Asian Integrated Model, 436 Asperg~llis, 375 Assimilate, see also Photosynthate in grain filling, 98 mobilization under water stress, 129-130 Assimilation efficiency, microbial, 371 Atmosphere-Ocean System model, 438 Atmospheric Global Circulation Models, 426-427, 428, 429, 431 Australia southern oscillation index, 121-122 wheat breeding in, 98-102, 187 wheat production in, 17-18, 95, 124, 134, 137 Australian plague locust, 242 Avena, 6, 150, 210, 297 Axial conductance, trade-offs in, 187-188 Azotobacter, 375 Bacillus toxin, 259 Bacteria, in soil communities, 378-381 Bacterial blight, in rice, 205 Balansia, 212

Ball-Berry equation, 44-45 Barberry, 212 Barley asynchronous development, 7 biomass partitioning in, 23 composite crosses and, 209 evapotranspiration and, 124, 125-126 fertilizer banding in, 315 leaf area growth in, 87

leaf gas-exchange efficiency in, 83 mixed cropping and, 225 nitrogen acquisition in, 21-25, 161-162 powdery mildew, 205, 208, 209, 225 preanthesis assimilation in, 129-130 scald, 209 selection strategies, 9, 11, 12, 17 in weed suppression, 307 wild progenitors, 21 yield in, 98 Barnyard grass, 307 Basic Linked System, 431-432 Bavaria, 9 Bean carbon isotope discrimination, 103 genetic diversity, 11 leaf gas-exchange efficiency in, 83 root architecture in, 185-186 in triculture, 270 weeds and, 325 yield in, 103 Beanfly, 262 Berberis, 212 Beta, 297

Biodiversity, see also Crop diversification in agriculture, 203 disease control and, 204 landscape heterogeneity and, 249, 272, 274 in modeling global changes, 445 pest resistance and, 243 Biogeography applications to plant-arthropod interactions, 248-250 modeling, environmental change and, 418-421 Biomass aboveground, in water-use efficiency, 118, 125-128 optimization in dryland agricultural systems, 131-133 partitioning, 23, 64-68 production, 94-97, 107-109 transpiration and, 122 wheat, 18 Biosphere, feedbacks in, 433-436 Blackman curve, 54 Black Turtle bean, 327 Blast, in rice, 218 Blister rust, 212 Blue-light receptors, nitrate uptake and, 157

Index

Boll weevil, 247 Borate, toxicity, 158 Box models, 421 Brachypodium, 179 Branching, in roots, 184-185 Brassica, 265, 298, 305, 309, 315, 328 Brassica, isothiocyanates in, 264 Breeders, legal protection for, 221-223 Breeding, see also Crop improvement; Selection carbon isotope discrimination and, 98-103, 109-111 in cowpea, 104-107 durable resistance and, 218-219 "evolutionary method," 219 future directions, 69-70 for interspecific mixing, 220-221 for intraspecific diversity, 219-220 photosynthesis and, 39-40 resistance genes and, 207 root traits and, 178, 185-186 soil fertility and, 25 stress resistance, 29 systems analysis in, 68-69 in wheat, 98-103 yields and, 9-12 Bremia, 227 Bromus, 7, 194, 298, 314 Buffalo grass, 186 Bulk selection, 220 Cabbage butterfly, 262 Calcium, deficiency, 158 California cowpea in, 104-107 wheat in, 95 CAM pathway, 447 Cannabis, 305 Canopy, see also Leaf early closure, 39, 51 effects on environment, 47-48 evapotranspiration and, 124-126 light interception, 50 light use efficiency, 53 photosynthetic rate, 42 water-use efficiency in, 85-88 wheat, 16, 18 Carbohydrate, see Assimilate; Photosynthate Carbon, see also C:N ratio; Soil carbon allocation, 85, 175-177, 180-183 in cost-benefit analyses, 175 in dark respiration, 85

455

density, 421 flow, microbial, 369-376 inputs to soil carbon flow, 382-383 loss, microbial metabolism and, 375 in photosynthetic oxidation and reduction, 41 in whole plant respiration, 84-85 Carbon cycle, modeling, 421-422, 433-436 Carbon dioxide, see also Greenhouse gases in climate change scenarios, 424-427 fertilization effect, 447-448 global emissions, 416, 417 in global environmental change models, 421,423, 431-432 IMAGE 2 modeling of, 435-436 leaf concentration, 40, 43, 44, 45 in leaf gas-exchange efficiency, 81-84 microbial production, 370, 373, 375 net uptake, carbon isotope discrimination and, 95-96, 107 nitrate assimilation and, 156 in photosynthesis, 56 Carbon gain, wheat, 16 Carbon isotope discrimination biomass production and, 94-97 in breeding, 98-103, 109-111 gas-exchange efficiency and, 91-92, 96-97, 107, 108-109 in grain legumes, 103-109 in peanut, 92, 93, 107-109 in small grain cereals, 94-103 water-use efficiency and, 79-80, 92-94, 111 yield and, 97-98, 111 Carrizo citrange, 188-189 Carrot fly, 270 Carthamus, 322 Cation:anion ratios, nitrogen source effects, 158 Cavitation, 187-188 Cellulose, decomposition, 387 Cell wall, pH effects and, 161 Centaurea, 327, 329 CENTURY model, 394-395 Cereal leaf beetle, 252 Cereals, see also Grain carbon isotope discrimination studies in, 94-103 intercropping in, 216 preadaptations, 6 CERES model, 423

456

Index

Chara, 150 Chemical defenses, see Defensive compounds Chenopodium, 299, 310, 323 Chick pea, sowing date, 88 China, intercropping in, 216 Chlorophyll, mutations, 52 Chortoicetes, 242 Cicer, 88 CIMMYr, 102 Citrus, 176, 190 Citrus root system absorptive vs. structural roots, 186 droughty soils and, 181, 182-183 fungal pathogens, 189-190 general characteristics, 174 life span, 194 mycorrhizae and, 191-193 proliferation in, 179 specific root length and hydraulic conductivity, 188-189 Clay extracellular compounds and, 376 in soil carbon flow, 392 Climate, Mediterranean carbon isotope discrimination studies and, 101-103 crop evolution in, 4-8 evapotranspiration in, 124-126 rainfall patterns, 119-120 Climate change, see also Global environmental change assumptions in, 424-428 effects on agriculture, 422 world food supply and, 430-433 Clonal propagation, in domestication, 5 Clover, 249, 250, 329 in weed management, 309, 322-324 in wheat intercropping, 216 C: N ratio in bacteria and fungi, 379 in cultivated and natural systems, 397 effects on decomposition, 387 Cochliobolus, 205 Cocklebur, 300, 318-319 Coevolution, host-pathogen, 206-212 Coffea, 205, 319

Coffee intercropping in, 225 rust, 205 weed control in, 319-320

Coleomegilla, 263, 270 Colletotrichum, 220

Colombia, intercropping in, 225 Community composition effects of pathogens on, 211 soil, 378-381 Companion planting, 217 "Compensatory growth," 61-62 Competition in agroecosystems, 296 in crop-weed interactions, 301-307 weed management and, 325, 328 Composite crossing, 209, 219 Conductance, stomatal, see Stomatal conductance Conservation tillage, 123-124 Consumer, responses to field mixtures, 225-226 Convective-conductive cooling, 45 Corky-root disease, 190 Corn, see Maize Corn earworm, 253 Corn rootworm, 246-247 Cortex, in root shedding, 182 Cost-benefit analysis in leaves, 64-65 of plant activities, 175 Cotesia, 264 Cotransport, in nitrate uptake, 154, 161 Cotton carbon isotope discrimination in, 110 crop-pest phenology in, 244 early termination practices, 245 gas-exchange efficiency in, 84 GOSSYM model, 40 induced resistance in, 259 leaf photosynthetic capacity in, 83-84 transpiration, 28-29 Cotton aphid, 246 Cotton leafhopper, 246 Counterresistance, in pests, 251,259 Cover crops improving nitrogen availability, 355 in weed management, 307-309 Cowpea, 103-107 C~ plants carbon dioxide fertilization effect, 447, 448 carbon isotope discrimination in, 91-92 gas-exchange efficiency in, 92 leaf carbon dioxide levels, 56

Index

photosynthetic quantum yield, 54 photosynthetic rate in, 43-44 C4 plants ambient carbon dioxide and, 447 photosynthetic quantum yield, 54 Cranberry, nitrogen source and, 158 "Critical weed-free period," 299 Cronartium, 212

Crops compared with wild progenitors, 12-27 distribution, biogeographical modeling, 420 early termination practices, 247 effects on environment, 8, 4 7 - 4 8 as herbivore resource, 242-243 inputs to soil carbon, 382-383 nitrogen demands, 351-353 nitrogen efficiency in, 350-351 origins, 3-5, 48-49 wild germplasm and, 27-31 Crop density, 39, 125, 316, 317, 329 Crop diversification abiotic stresses and, 217 consumer response to, 225-226 crop management and, 223-225 cultivar mixtures, 213 effects on plant-arthropod interactions, 263-264 farmers and, 223 future perspectives, 228 government support and, 227-228 interspecific, 216-217 intraspecific, 212-216 legal issues, 222-223 multilines, 212 near-isogenic line mixtures, 212 permaculture, 217 technical aspects, 226-227 Crop improvement, see also Breeding; Selection carbon isotope discrimination in, 109-111 future directions, 69-70 gas-exchange efficiency and, 79-81 molecular genetics, 29-31 photosynthesis and, 68-70 salt tolerance, 30 systems analysis in, 68-69 Crop management contributing to pest outbreaks, 240-241 crop diversification strategies in, 223-225 in dryland agricultural systems, 117, 119, 134-137

457

for nitrogen, 361-362 soil carbon and, 399-402 Crop performance, water-use efficiency and, 118 Crop-pest phenologies, 244-246 Crop productivity, see also Yield models, 418, 421-423 water-limited, 118-119 Crop rotation, 224 modeling of, 136 in pest management, 246-247 in weed management, 307, 327-328, 329 Crop transpiration efficiency, 80, 86 Crop-weed interactions, see also Weed management competition in, 301-307 "critical weed-free period," 299 crop density and, 316, 317, 329 leaf area in, 299-300, 324-325 legumes in, 316 modeling, 301-304, 306-307, 327 nitrogen availability and, 304 propagule dispersal and, 301 soil temperature and, 318 weed emergence and, 298 weed spatial distribution and, 300-301 weed suppression and tolerance in, 303-304, 324-325 yield loss relationships, 297-300 Cross-pollination, in domestication, 5-6, 7-8 Crown rust, in oats, 211,218-219, 224-225,~ Cucumber, herbivores and, 264-265 Cucumber beetle, 257 Cucurbitacin, 257, 264-265 Cultivars, mixtures, in crop diversification, 11,212 Cultivation effects on denitrification, 360 effects on soil fungal biomass, 380 effects on soil organic matter, 401 soil carbon losses and, 399 in weed management, 309, 310-311,330 Curly-top virus, 62 Cyperus, 293, 298, 304 Dactylis, 179, 194

Dark respiration, 85 Datura, 316

Decomposition in carbon cycle modeling, 434 of cellulose, 387

458

Index

edaphic factors in, 387-388 of lignin, 387, 401,402 management of, 400-401 of plant components, 391 of polysaccharides, 376 rates, in soil carbon flow, 386-388 Defensive compounds, 258-260 costs, 62-63 in herbivore attraction, 264-265 trade offs with growth, 189-190 Denitrification, in nitrogen loss, 349, 360 Densitometry, in soil analysis, 385 Desiccants, in drought simulation, 130 Development, asynchronous, 7 Diabrotica, 246-247, 257 Diaphania, 269 Dichotomous branching, in roots, 184-185 Diffuse light, 52 DIMBOA, 256, 258 Disease in monocultures, 203-205 in natural ecosystems, 210-211 pathogen migration and, 209 and photosynthesis, 62 Disease control biodiversity and, 204 crop diversification and, 212-217 durable resistance and, 205-206 hygiene and, 214-215 regional gene deployment, 224-225 threshold density and, 214-215 Disease resistance, see also Plant defenses biodiversity and, 204 durable resistance, 205-206, 218-219 herbivore counterresistance and, 251, 259 induced, 258 in pest management, 274-276 Diversity, see Biodiversity; Crop diversification Domestication, 3-8 Douglas fir, 306 Downy brome, 314-315, 320, 324 Downy mildew, 217, 227 Drinking water, herbicide contamination, 292 Drought in carbon isotope discrimination studies, 104 chemical simulation, 130 in dryland agricultural systems, 117, 119-120

responses, 57-79 terminal, 120, 130 Drought resistance, cavitation and, 187-188 Dryland agricultural systems biomass optimization in, 131-133 crop productivity in, 118-119 management strategies in, 117, 119, 134-137 rainfall in, 90-91,117, 119-120 rainfall prediction and, 120-122, 137 transpiration efficiency in, 126-127 transpiration in, 122-126 yield in, 127-128, 131-133, 134-137 Dry matter, distribution, 88 water stress and, 127-130 Duncan grapefruit, 188-189 Durable resistance, 205-206, 218-219 Dwarfing, 39, 49, 52 Early successional plants, herbivores and, 243-244 Earthworm, 224 Echinocloa, 297 "Ecological combining ability," 219 "Ecological weed management," see Weed management Economic analysis, of plant activities, 175 Ecophysiology in domestication, 4-8 fitness and, 48-49 genetic diversity and, 27-31 selection strategies and, 12-27 Ecosystems, see also Agroecosystems disease levels in, 208-209 host-pathogen coevolution in, 210-212 interactions with agroecosystems, 212 modeling, with linked models, 418-423 Ecotypes, in domestication, 6-7 Einkorn wheat, 13 EIS model, 437 Electron transport chain, 18, 55 E1 Nifio, 121 Elytrigia, 304 Embolism, 187-188 Emmer wheat, 13 Endophytes, symbiosis and, 211 Energy-Industry System model, 437 ENSO, 121 Environment, see also Ecosystems agricultural vs. wild, 49 consequences of global change, 70

In~x

effects of crops on, 8, 47-48 effects on photosynthesis, 42-43 plant optimization in, 49 EPIC model, 429 Epidermis, in root shedding, 182 Epilachna, 269 Erigone, 270 Erysiphe, 205, 208 ESCAPE model, 426 Eucalyptus, photoinhibition in, 56 European corn borer, 242, 256 European stem borer, 216 Evaporation, see also Evapotranspiration in dryland agricultural systems, 119 in gas-exchange efficiency, 89, 90-91 reduction, 124-126 in water-use efficiency, 80, 86-87, 118 Evapotranspiration, see also Evaporation; Transpiration in dryland agricultural systems, 124-126 in nitrogen leaching, 359 in water-use efficiency, 118 "Evolutionary plant breeding," 219-220 Extracellular compounds, 376 Exudates in predator recruitment, 267 root, 383 Fallow, soil organic matter and, 400 Farmers, crop diversification and, 223 Farming, see Agriculture FCCC, see Framework Convention on Climate Change Feedback, in terrestrial biosphere, 433-436 Ferocactus, 187 Ferredoxin, 155 Fertilizer application, field-scale effects and, 356-358 banding, 314-315, 356 contemporary use, 11,347-349 in dryland agricultural systems, 135-136 effects on nitrogen use efficiency, 353 evapotranspiration and, 125 soil organic carbon and, 400, 401 synthetic nitrogen in, 352 weed management and, 314-316, 319 Festura, 194 Fiddleneck, 320 Field, soil variability in, 356-358 Field mixtures, consumer responses to, 225-226

459

Fire, in nitrogen loss, 358-359 Fitness in coevolution, 206-207 ecophysiology and, 48-49 Flag leaf, 15, 53 Flame weeding, 311 Flax resistance genes in, 208 rust, 208, 210 Flea beetle, 265-266 Flowering effects on yield, 97-98, 110 water-use efficiency and, 88 Food supply, global, climate change and, 430-431 Food web, soil, 381-382 FORENA model, 429 Forestry, multiuse, 217 Forest succession, modeling, 420 Foxtail, 309 Fractionation, in soil analysis, 384 Framework Convention on Climate Change, 416, 440 Frankliniella, 246 Freezing damage, 60 Fruit characters, water stress and, 131 thinning, 51 Fumigation-incubation method, 399 Functional diversity, 213 Fungi, see also Mycorrhizae; specific types decomposition of, 375 root pathogens, 189-190 in soil community composition, 378-381 Furanocoumarin, 257 Gaeumannomyces, 224 Gas-exchange efficiency canopy, 85-88 carbon isotope discrimination and, 91-92, 96-97, 107, 108-109 in crop improvement, 79-81 defined, 80 leaf, 26, 81-84 water availability and, 89-91 whole plant, 84-85 yield and, 101-102 GCAM model, 427 Genes, see also Resistance genes dwarfing, 18 identification and mapping, 30-31 pyramids, 218

460

Index

Genetic diversity disease resistance and, 204 landraces, 9, 10-11 wild germplasm and, 27-31 Genetic drift, in nonagricultural coevolution, 210 Genetic erosion, 222 Germany crop rotation in, 224 intercropping in, 225 Germany, East, intercropping in, 223 Germplasm, wild, 27-31 GFDL model, 431 GHG, see Greenhouse gases GISS model, 428, 431 Global environmental change assessment for agriculture, 420, 424-433 future research, 445-446 greenhouse gases and, 416-417, 424-427, 438, 440, 442-443 human activity and, 415 modeling with integrated models, 436-445 with linked models, 418-425 Glomus, 191

Glucosinolate, 257-258 Glutamate synthase, 151-152 Glutamine inhibition of ammonium uptake, 152-153 inhibition of nitrate uptake, 157 Glutamine synthetase, 151-152 Glycine, 84 Goat grass, 314-315 GOSSYM model, 40, 69 Gossypium, 83, 84, 311 Government, crop diversification, support of, 227-228 Grafting, 5 Grain, see also Cereals filling, 98, 132-133 preadaptations, 6 size, in wheat, 19-20 yield forecasts, 431-432 Grain legumes, 103-109 Grapefruit, 181, 188-189 Grasses, domestication, 6-7 Greenbug, 251 Green cloverworm, 270 Greenhouse effect, see Global environmental change; Greenhouse gases

Greenhouse gases in climate change scenarios, 424-427 forecast increases, 416-417, 438, 440, 442-443 Green leaf hopper, 224 Green manure, 224 Groundsel, 320-321 Growth, see also Relative growth rate agricultural vs. wild, 48-49 carbon dioxide fertilization effect, 447-448 "compensatory," 61-62 nitrogen source effects, 158-159 trade offs with defense, 189-190 use of photosynthate, 64-67 water availability and, 89-91 Gryon, 267 Gymnosporang~um, 212 Habitat, see also Ecosystems effects of crops on, 8, 47-48 Hairy vetch, 308 Hardening, 60 Harvest index, 65, 66, 68 carbon isotope discrimination and, 97-98, 108-109, 111 in cowpea, 105 in dryland agricultural systems, 118-119, 132 transpiration efficiency and, 126 water stress and, 130-131 in wheat, 19 yield and, 131 Harvesting, of mixed crops, 226 Heat, leaf temperature and, 45 Helianthus, 25, 26, 87 Heliothis, 253, 263 Hemileia, 205 Herbicides drinking water contamination, 292 in ecological weed management, 295, 296, 328, 329 in pesticide poisoning, 292 resistance to, 293 world use, 291-292 Herbivores, see Arthropods, phytophagous Herbivory effects on photosynthesis, 60-62 plant nitrogen levels and, 260-263 on roots, 189-190 Herringbone branching, in roots, 184-185

Index

Hessian fly, 224, 244 Hippodamia, 263 Holeus, 194 Hordeum, 7, 21, 23, 83, 208, 297 Host-pathogen coevolution, 206-212 Human activity, global impact, 415 Humic acid, 391 Humic material, 383-384 Humidity, photosynthetic rate and, 43, 44, 45, 46 Humin, 382 Hybridization, in stress resistance, 29 Hybrids, in modern agriculture, 49 Hydraulic conductivity, in roots, 186-189 Hygiene, 214-215 IAM models, 417-418, 427 Ideotypes, 69 IMAGE 1 model, 427 IMAGE 2 model, 418, 427, 435 goals, 437 scenario simulations with, 440-445 structure of, 436-440 subsystem models, 437-438, 439 Inbreeding, in domestication, 6 Incident irradiance, see Irradiance Induced resistance, 258 Infiltration, 122-124 Inopus, 247

Insectary plants, 267 Insect control, see Pest management Integrated assessment models, 417-418, 427 Integrated farming practices, 224 Integrated Model to Assess the Greenhouse Effect, see IMAGE 1model; IMAGE 2 model INTERCOM model, 306, 326 Intercropping, 216-217, 220-221,223 harvesting and, 226 in pest management, 265-266 predator recruitment and, 269-272 in weed management, 317-318 with weeds, 270-271 Interference, in agroecosystems, 296 Intergovernmental Panel on Climate Change, 416, 417, 418, 428, 440 IPCC, see Intergovernmental Panel on Climate Change Ipomea, 322 Irradiance, 50; see also Light leaf acclimation to, 55-56

461

penumbral effects, 53 photosynthetic rate and, 43-44, 54-55 transpiration efficiency and, 126-127 Irrigation carbon isotope discrimination and, 102, 103-104 in weed management, 313-314, 319 Island biogeography, applications to plantarthropod interactions, 248-250 Isothiocyanate, 264 Jacobs Cattle bean, 325 Johnson grass, 271 Johnson-Thornley equation, 44 Kenya, response farming forecasts in, 121 Knapweed, 327 Lactuca, 3, 185, 226, 320 Lambsquarter, 309, 322-323 Land agricultural, loss of, 228 heterogeneity, biodiversity and, 249, 271, 274 Landraces, 9-12, 222 Land use in carbon cycle modeling, 435 global environmental change and, 415, 421, 433, 440, 441-442 Lophopyrum, 30 Late blight, 204-205, 224 Leaching in nitrogen loss, 359-360 of soil carbon, 399 Leaf, see also Canopy acclimation to irradiance, 55-56 anatomy, wheat, 15-16 architecture, wheat, 19 cost-benefit analysis, 64-65 display, 51 erectness, 39, 50-51, 84 flag, 15, 53 gas exchange efficiency, 28, 81-84 growth, 26, 87-91, 126, 128 internal carbon dioxide concentration, 40, 43, 44, 45 light interception, 49-53 long lived, traits of, 177-178 paraheliotropism, 84 photosynthetic capacity, 81-84, 87 reflectivity, 84 solar tracking, 52

462

Index

toughness, 252 water-use efficiency in, 81-84 Leaf angle distribution, 50, 51, 52, 54 Leaf area, 16, 18, 50 in crop-weed interactions, 299-300, 324-325 display, 26 estimation, techniques in, 300 growth, 87-91,126 water stress and, 127-128 Leaf area index, 42, 50, 51, 52, 324 herbivory and, 61, 62 transpiration efficiency and, 127 water use efficiency and, 58 Leaf area ratio, 41 Leaf blight, in maize, 205 Leafhopper, 246 Leaf photosynthetic capacity, 81-84, 87 Leafroller, 247 Leaf:shoot mass ratio, 65 Leaf spot disease, 62, 211 Leaf temperature, 45, 52, 59-60 in gas-exchange efficiency, 83 in photoinhibition, 55-56 Leaf weight ratio, 42 Legislation, crop diversification issues, 222-223 Legumes carbon isotope discrimination studies in, 103-109 in crop-weed interactions, 316 in nitrogen cycling, 349-350 in weed management, 322-324 Lemna, 150 Lemon droughty soil and, 183 mycorrhizae and, 191-193 Lepidopterans, 246; see also specific types LESS-BI model, 441 Lettuce, 3, 28 downy mildew, 227 fertilizer banding in, 314 intercropping and, 226-227 root architecture in, 185 root pathogens and, 190 weed management in, 314, 320-321 Light, see also Irradiance diffuse, 52 interception, 49-53 nitrate reductase activity and, 157-158 nitrate uptake and, 157

photosynthetic rate and, 43-44 secondary plant metabolites, effects on, 260 Light use efficiency, 53-56 Lignin, in decomposition, 387, 401,402 Linum, 208 Lodging, 88 Lolium, 182, 319 Longitarsus, 321 Lucerne leafroller, 247 Lycopersicon, 252, 297 Macroaggregates, in soil carbon flow, 389-392 Magnesium chlorate, 130 Maintenance coefficient, microbial, 373-374 Maintenance respiration, 63-64 microbial, 372-374 Maize domestication, 7-8 downy mildew, 217 leaf blight, 205 rotation with soybean, 246-247 in triculture, 270 weed management in, 299, 300, 304, 322 "Maize-ley" system, 216 Malt, intercropping and, 225 Manduca, 264 Marafax bean, 325 Marigold, 217 Markov chain, 121 Mass spectrometry, radio isotope, 93 Mayeticola, 224 Mayweed chamomile, 318 Meat production, in MINK study, 430 Medicago, 314 Mediterranean annuals, 4-7, 27 Mediterranean climate carbon isotope discrimination studies and, 101-103 crop evolution in, 4-8 evapotranspiration in, 124-126 rainfall patterns, 119-120 Melampsora, 208 Membrane potential ammonium and, 147, 150-151 nitrate uptake and, 154 Merophyas, 247 Methane, 370, 401 Mexican bean beetle, 269

Index

Mexico intercropping in, 270 wheat in, 102 Michaelis-Menten kinetics, in ammonium uptake, 148 Microaggregates, in soil carbon flow, 391 Microorganisms biomass assessment, 377-378, 399 carbon flow in, 369-376 decomposition of, 375 extracellular compounds, 375-376 phospholipid fatty acid analysis, 380-381 plant pathogens, 203-228 respiration assay, 386 soil carbon flow and, 375-385, 394-396, 398-399 in soil food web, 381-382 soil moisture and, 388 as soil nitrogen pool, 397-398 soil particles and, 392-383 soil pore size and, 389 temperature and, 388 yield coefficient, 371-372 Migration in disease movement, 209 of herbivores, 242 MINK study, 429-430 Mistletoe, 62 Mites as phytophagous arthropods, 241 predaceous, 263, 267 in soil food web, 382 Miticides, economic costs, 241 Mixed cropping, see Intercropping Mixing ability, 219 M l a l 3 gene, 208 Mlg gene, 208 Modeling, see also specific models in crop-weed interactions, 301-304, 306-307, 327 in dryland management, 136 of global environmental change 9 with integrated models, 436-445 with linked models, 418-423 of microbial maintenance respiration, 374 process-based, 69 of soil carbon flow, 393-396 of soil food web, 381-382 Molecular genetics, in crop improvement, 29-31

463

Molybdate, toxicity, 158 Monocarboxylmonoamino acid, 150 Monocultures disease and disease control in, 203-206 historical development, 203 host-pathogen coevolution in, 206-209 nitrogen availability in, 354-355 pest outbreaks in, 249-250 predator recruitment and, 269-271 weed management in, 327-328 Moroberekan rice, 219 Mosaic virus, 62 Multivoltine herbivores, 242, 244-245 Mustard, wild, 305, 325 Mustard beetle, 252 Mutations, low-chlorophyll, 52 Mycorrhizae, costs and benefits of, 190-193 NADH/NADPH in ammonium assimilation, 152 in nitrate assimilation, 155 Natural selection, 3 Nectaries, extrafloral, 267 Neighborhood effects, 219 Nematodes, 320 companion planting and, 217 root architecture, effects on, 192 in soil food web, 382 Nephotettix, 224 Net Ecosystems Productivity, 434 Net primary production, 415, 421,434 Nitrate acquisition, 22, 153-158, 161-162 assimilation, 155-156, 158 effiux, 157 leaching, 359 membrane depolarization and, 154 movement in soil, 163 in nitrogen cycle, 349 as nitrogen source, 153 plant growth and, 158-159 root growth and, 159-160 storage, 158 Nitrate reductase, 155, 156, 157-158 Nitrification, inhibitors, 355 Nitrite, 155-156 Nitrite reductase, 155 Nitrogen, see also Ammonium; Nitrate acquisition, 21-22, 145-146, 151, 155-156 crop demands, 351-353 cycle, 349-350

464

Index

in dryland agricultural systems, 135-136 effects on secondary plant metabolites, 257-258 efficiency, mechanisms of, 350-351 loss, 350, 351,358-360 management in row-crop systems, 361-362 plant levels, herbivory and, 260-265 pool, microorganisms as, 397-398 soil levels, weed management and, 318-319 in soil organic matter, 351-352 source effects, 158-159 synthetic, 352 uptake and partitioning, barley, 22-25 vegetative-reproductive transition and, 67 Nitrogen availability, 23, 25 cover crops and, 355 effect of weeds on, 304 field-scale effects, 356-358 in monocultures, 354-355 in nitrogen cycling, 350 nitrogen use efficiency and, 252 root growth and, 159-160 row-interrow effects, 355-356 synchronizing with demand, 353-355 in tropical soils, 355 Nitrogen fixation, 108 Nitrogen harvest index, 163 Nitrogen use efficiency, 59 defined, 352-353 effects of fertilizers on, 353 nitrogen availability and, 252 Nuclear magnetic resonance, in soil analysis, 384 Nutrients effects of tillage on, 356 in photosynthesis, 59 plant levels, pest management and, 260-263 scavenging of, 64 Nutrient-use efficiency, 59 Nutsedge, 298, 304, 305 Oat-frit fly, 215 Oats crown rust, 211,218-219, 224-225, wild, stem rust, 210 Ocean circulation models, 427 Oilseed rape, 265-266 Okra, leaf photosynthetic capacity in, 83-84

Operational costs, 66-67 Ophiomyia, 262 Orchards, 274 Organic farming, 293, 381 Or/us, 263, 270 Oryza, 218, 304

Oscinella, 215 Osmotic adjustment, 128 Ostrinia, 216 Oulema, 252 Outcrossing, in domestication, 5-6, 7-8 Oxidation-reduction reactions in photosynthesis, 41 in soil microorganisms, 382

Panicum, 211 Panonychus, 263 Paraheliotropism, 84 Parasitoids in plant-arthropod interactions, 263-264 recruitment, in pest management, 266-271 Pathogens coevolution in, 206-212 crop diversification and, 214 effects on host community composition, 211 effects on root growth and defense, 189-190

migration of, 209 "super races," 215 in weed management, 311-312, 320-321 Pea, in weed suppression, 305 Peanut biomass production, 107-109 carbon isotope discrimination in, 92, 93, 107-109 leaf area growth in, 87 nitrogen fixation, 108 water-use efficiency and, 111 Pearl millet, 130, 220 Pear rust, 212 Pennisetum, 220, 322 Perennials, root traits, 174 Permaculture, 217 Peronosclerospora, 217 Pests, see Arthropods, phytophagous Pesticides economic costs, 241 poisoning, 292

Index

Pest management, see also Plant-arthropod interactions Bt toxin in, 259 colonizer pools, 248-249 crop-pest phenologies and, 244-246 crop rotation in, 246-247 disease resistance and, 274-276 diversification strategies and, 215, 224 early termination practices, 247 ecological principles and, 239-240, 271, 274-276 economic costs, 241 herbivore counterresistance and, 251, 259 intercropping and, 265-266 plant nutritional levels and, 260-263 predators and parasitoids in, 263-264, 269-271 reducing plant apparency, 264-266 resistance genes and, 259-260 returns on investment, 240 pH in ammonium toxicity, 149 in ammonium uptake, 151 cell wall extension and, 161 nitrate uptake and, 154 Phaedon, 252 Phalaris, 314

Phaseola toxins, 62 Phaseolus, 185, 297, 314, 326 Phenology crop-pest, 244-246 in water-use efficiency improvement, 87-88, 98 Phenotypic plasticity, in domestication, 5-7 Phloem, transport costs, 66 Phospholipid fatty acid analysis, 380-381 Phosphorus, uptake, mycorrhizae and, 190-193 Photoinhibition, 55-56 Photon flux density, 53 Photoperiod, vegetative-reproductive transition and, 67 Photosynthate, see also Assimilate allocation patterns, 62-68 Photosynthesis in acclimation, 46-56 breeding and, 39-40 capacity vs. rate, 42 carbon dioxide use, 56 conversion efficiency, 41

465

crop improvement and, 68-70 effects of stressors, 62 environmental variations and, 42-43 gross, 40-41 herbivory and, 60-62 light use in, 49-56 net, 40-41 nutrient use in, 59 per leaf unit, 41-42 quantum yield, 53-54 temperature modulation of, 43-46, 54, 55, 59-60 water use, 40, 42, 56, 57-59, 85 Photosynthetic capacity carbon isotope discrimination and, 81-84, 96, 102, 107-108 leaf, 81-84, 87 water availability and, 89-91 in wheat evolution, 15-17 Photosynthetic flux density, 156 Photosynthetic rate canopy, 42 environmental and physiological influences, 43-46 irradiance and, 43-44, 54-55 in wheat, 14-18 whole plant, 42 yield and, 28 Physical protection, in soil carbon flow, 388-389 Physiological traits in acclimation, 46-49 affecting evapotranspiration, 125-126 genetic variation in, 27-31 selection strategies and, 12-27 yield and, 28 Phytochrome, 157 Phytoecdysone, 256-257 Phytophthora, 186, 189-190, 204-205, 220 Phytophthora rot, 220 Pieris, 260 Pigweed, 299, 304, 309 Pima cotton, 28, 84, 110 Pine, 193, 212 Pineapple, 188-189 Pinus, 212 Pisum, 305 Plant-arthropod interactions, see also Pest management counterresistance and, 259 crop diversity and, 265-266

466

Index

development of research in, 239 island analogy in, 248-250 in pest management, 239-240 plant nutritional levels and, 260-263 predators and parasitoids in, 263-264 Plant compounds, see also Assimilate; Photosynthate defensive, 62-63, 189-190, 256-260, 264-265 Plant defenses, see also Defensive compounds; Disease resistance chemical attributes, 253-256 early successional plants and, 243-244 inducible resistance, 258 morphological, 251-253 plant nutritional levels and, 260-263 predator recruitment, 266-271 resource allocation to, 250-251 trade offs with growth, 189-190 Planting density, 39, 125 Plant Varietal Protection Act, 222, 223 Plant volume, in predicting crop-weed interactions, 300 Plasmalemma, depolarization, 147, 150-151,154 Plasticity, phenotypic, in domestication, 5-7 Plastids, in ammonium assimilation, 152 Ploidy levels, wheat, 13 Poland, intercropping in, 216, 220-221, 223 Politics, crop diversification and, 227-228 Polyculture, see Intercropping Poly-/3-hydroxybutyrate, 374-375 Polysaccharides, decomposition of, 376 Poncirus, 188 Potassium ammonium uptake and, 151 deficiency, 158 uptake, 160-161 Potassium iodide, 130 Potato cover crops and, 309 glycoalkaloid production, 258 late blight, 204-205, 224 Powdery mildew in barley, 205, 208, 209, 225 intercropping and, 223 Prairie, tallgrass, carbon flow in, 396 Preadaptation, 5, 6 Preanthesis assimilates, 129-130

Precipitation, see also Rainfall forecasting, 120-122, 137 Predators in plant-arthropod interactions, 261-264 recruitment, in pest management, 266-271 in weed management, 311-312, 320-321 Production efficiency, microbial, 371 Progenitors, see Wild plants Propagation, clonal, in domestication, 5 Protonmotive force, in nitrate uptake, 154 Pseudomonas, 320 Pseudotsuga, 306 Psila, 270 Puccinia, 205, 207, 208, 210, 211,212, 320-321 Pyricularia, 218 Pyrolysis, analytical, in soil analysis, 384 Pythium, 190 Quackgrass, 304, 305 Quantitative trait loci, 30-31 Radiative cooling, 45 Radiocarbon dating, of soil organic matter, 391,397 Radio isotope mass spectrometry, 93 Radish, 158 Ragwort, 321 Ragwort flea beetle, 321 Rainfall in carbon isotope discrimination studies, 96-97 in dryland agricultural systems, 90-91, 117, 119-120 forecasting, 120-122, 137 Rapeseed, 309 Raphanus, 328 Red alder, 306 Red clover, 249, 250 Relative extension rate, in roots, 179 Relative growth rate, 41 leaf: shoot mass ratio and, 65 root: shoot ratio and, 65-66, 175 root tissue density and, 179 Relative water content, 59 Reproduction allocation, 67-68 ammonium and, 158-159 Reproductive isolation, 3-4 Reproductive mass, 65

Index

Reserves, see Assimilate Residues burning, nitrogen loss and, 358-359 decomposition in, 387 inputs to soil carbon, 383 soil microbial communities and, 379 soil water and, 123-124 in weed management, 307-309, 321-324 Resistance genes in breeding, 207 in coevolution, 208 in disease control, 212-217 recycling, 224 regional deployment, 224-225 strategies for use, 259-260 Resource acquisition, in acclimation, 48, 49 Resource allocation in acclimation, 48 breeding and, 12 effects of domestication on, 7 patterns, 62-68 physiology and, 14-21 to plant defenses, 250-251 in roots, 175-177, 180-183 Resource availability, yield and, 8 Resource competition, in crop-weed interactions, 301-307 Resource truncation, 247 Respiration dark, 85 microbial, 370, 372-374 partitioning, 62-64 photosynthesis and, 40-41 root, 176-177, 181-182 in wheat, 18 whole plant, 84-85 Respiration assay, microbial, 386 Rhamnus, 218 Rhizobacteria, 320 Rhizoctonia, 224 Rhizomonas, 190 Rhizosphere, 146-147, 152 Rht genes, 18 Rhynchosporium, 209, 212 Ribes, 212

Ribulose-l,5-bisphosphate carboxylase oxygenase, see Rubisco Riccia, 150 Rice bacterial blight in, 205 blast, 218

467

durable resistance in, 219 green leaf hopper resistance, 224 weed management in, 304, 307, 321, 324-325 Ridge pineapple, 190-191 Ridge tillage, 356 Risk management, in acclimation, 48, 49 Roots, see also Citrus root system; Specific root length absorptive vs. structural, 186 allocation, 19, 65-66 ammonium acquisition, 146-153, 160-163 architecture, 183-186 breeding and, 178, 185-186 carbohydrate levels, 153 carbon allocation to, 175-177, 180-183 defenses, 189-190 density, 103, 128 depth, 128 diameter, 178-180 efficiency, 183, 193 equilibrium with shoots, 159-160, 175-176, 177 exudates, 383 herbivory and pathogens, 189-190 hydraulic conductivity, 186-189 inputs to soil carbon, 382-383 length density, 103 life span, 193-194 mycorrhizae and, 190-193 nitrate acquisition, 153-158, 160-163 nitrogen acquisition, 21-22 respiration, 176-177, 181-182 shedding, 182 soil heterogeneity and, 180-183 in sunflower, 26-27, 128 tissue density, 178-180 topology, 184-185 tradeoffs in, 173-174, 194-195 Root growth acid, 161 construction costs vs. maintenance costs, 176-177 equilibrium with shoot growth, 175-176 nitrogen availability and, 159-160 relative rate of extension, 179 soil heterogeneity and, 181 water stress and, 128 Root hairs, 161 Root length density, 103 Root: shoot ratio, 65-66, 175, 382-383

468

Index

Root/soil respiration, 183, 192 Rootstocks, citrus, see Citrus root system Rothamsted Experiment Station, 394, 400 Row-crop systems, nitrogen management in, 361-362 Royalties, breeders and, 221 Rpsl-b gene, 220 Rps3 gene, 220 Rubisco, 40-41, 55, 87 Ruderals, in crop origins, 4-5, 48-49 Runoff, 119, 123-124 Rust, see also specific types in coffee, 205 in flax, 206, 210 in weed management, 320-321 in wheat, 208 Rwanda, 11 Rye grass, 182, 321 Salad leaf crops, 226-227 Salt tolerance, 30, 65 Scald, in barley, 209 Scelio, 242 Schizaphus, 251 Secale, 305 Secondary metabolites costs, 62-63 in herbivore attraction, 264-265 in plant defenses, 256-260 trade offs with growth, 189-190 Sedimentation, in soil analysis, 384 Seed density, in weed management, 316 partial replacement strategy, 220 predation, 311-312 Seedlings, nitrogen source and, 158 Seed weevil, 250 Selection, see also Breeding; Crop improvement agricultural, 8-12, 207-209 barley and, 17 physiological traits and, 12-27 plant adaptive strategies and, 29 Self-pollination, in domestication, 6 Senecio, 320-321 Senegal, 104 Senescence, cost-benefit analysis, 64, 65 Septoria, 216 Setaria, 309 Shading, in weed management, 319-320

Shoot, see also Root: shoot ratio equilibrium with roots, 159-160, 175-176, 177 leaf: shoot mass ratio, 65 nitrate assimilation in, 155-156 Sieving, in soil analysis, 384 Silene, 211 Simulation models, in dryland agricultural system management, 136 Sinapsis, 315, 326, 328 Sitopsis, 13 Small-grain cereals, 94-103 Smut, 216 Soil droughty, root systems in, 181, 182-183 extracellular compounds in, 375-376 field-scale variability, 356-358 food web, 381-382 nitrate movement, 163 nitrogen pool, 397-398 pore size, 389 reduced conditions, microbial respiration and, 370 solarization, 312 tropical, nitrogen availability in, 355 Soil carbon climatic effects and, 398-399 losses, 375, 399 management of, 399-402 microbial metabolism and, 375-385 soluble fraction, 385-386 Soil carbon flow in agroecosystems, 367-369, 396-397 carbon inputs, 382-383 carbon pools in, 383-386 climactic factors and, 388 decomposition rates and, 386-388 edaphic factors in, 389-392 microbial biomass in, 377-378 microbial community in, 378-381 microbial respiration in, 373-374 in natural ecosystems, 396-397 physical protection in, 388-389 quantitative descriptions, 393-396 Soil fertility, effects on breeding, 25 Soil moisture effects on soil carbon flow, 388 in weed management, 313-314, 318-319 Soil organic matter age of, 391,397 analytical methods in, 384-385

Index

components, 383-384 management of, 400-402 nitrogen content, 351-352 physical protection in, 389 Soil particles, in soil carbon flow, 389-393, 394-396 Soil temperature, in weed management, 318 Soil water, 89-91 carbon isotope discrimination and, 94, 96, 103-104, 106 maximizing, 123-124 Soil water content, 58, 127 Solanum, 306 Solar tracking, 52 Soldier fly, 247 Sorghum, 84, 299, 304 Southern oscillation index, 121-122, 137 Sowing date evapotranspiration and, 124-125 in water-use efficiency improvement, 87-88 Soybean bulk selection in, 220 pubescence in, 84 rotation with corn, 246-247 weed management in, 299, 304, 318-319, 324 Spain, sunflower in, 124-125 Specific leaf area, 41, 87 in carbon isotope discrimination studies, 96, 108-109 Specific root length, 178-180 hydraulic conductivity and, 188-189 root life span and, 194 Spider mites, 258-259 Squash, in triculture, 270 Stagonospora, 209 Starthistle, 329 Stem rust in wheat, 207, 212, 225 in wild oats, 210 Stomata in leaf gas-exchange efficiency, 83 optimal function, 79 Stomatal conductance, 43, 44-45, 54 in canopy gas-exchange efficiency, 86 carbon isotope discrimination and, 95-96, 99, 102, 103, 106-107, 110-111

469

water availability and, 89, 90, 91 in water use efficiency, 57, 58 Storage carbohydrate, 63, 66 compounds, microbial, 374-375 of nitrate, 158 Strawberry, 193 Stress resistance, breeding for, 29 "Stress resistant syndrome," 10, 29 Strip cropping, 226 Stripe rust, in wheat, 205, 225 Subsistence agriculture, 9-11,223 Succession in crop origins, 5 forest, 420 herbivores and, 243-244 Succulents, root respiration in, 181 Sugarcane, early termination practices, 247 Sugarcane soldier fly, 247 Sulfonylurea, 293 Sunflecks, 54 Sunflower evapotranspiration and, 124-125 leaf area growth in, 87 model of crop rotation, 136 root system, 128 water relations, 25-27, 131 Swingle citrumelo, 188-189 Switzerland, crop diversification issues in, 222 Symbiosis, 211 Syria, 9, 11 barley in, 98, 124 Systems analysis, 68-69 Tadpole shrimp, 321 Tagetes, 217 Take-all, 224 Tallgrass prairie, carbon flow in, 396 Tannins, condensed, 256 Temperature, see also Leaf temperature effects on soil carbon flow, 388 global change, forecasts, 443 in leaf gas-exchange efficiency, 83 in photoinhibition, 55-56 in photosynthesis, 43-46, 54, 55, 59-60 soil, weed management and, 318 Terminal drought, 120, 130 Terrestrial biosphere, feedbacks in, 433-436 Terrestrial Environment System model, 437 TES model, 437

470

Index

Texas Boll Weevil Eradication Program, 247 "Texoka" grass, root architecture in, 186 Thea, 319 Theobroma, 319 Thermal damage, 60 Thinning, fruit, 51 Thinopyrum, 30 Threshold density, 214-215 Thrips, 246 Tillage effects on soil carbon flow, 392 effects on soil microbial communities, 379 effects on soil organic matter, 401 nutrient availability and, 356 reduced, 224 soil water and, 123-124 in weed management, 309, 311 Tissue density, root, 178-180 Tomato defenses in, 189, 252 production, crop-pest phenologies in, 245-246 weed management in, 318 Top crossing, 220 Toxins phaseola, 62 in plant defenses, 256, 257 Transpiration, 57 biomass and, 122 in carbon isotope discrimination studies, 96-97 cooling, 45 in cotton, 28-29 in dryland agricultural systems, 122-126 environmental control, 47-48 stomatal conductance and, 44 in water-limited conditions, 89-90, 118-119 in water-use efficiency, 81-83, 118 Transpiration efficiency crop, 80, 86, 118, 126-127 defined, 80 environmental factors and, 126-127 in gas-exchange efficiency, 84-85 harvest index and, 132 in water-use efficiency, 118 Transport, active of ammonium, 146-151

costs, 63, 64, 66 of nitrate, 153-155 Trees leaf display, 51 planting, ecological consequences, 228 Triazine, 293 Tricarboxylic acid cycle, 370-371 Trichomes, in plant defenses, 252-253 Triculture, 270 2-tridecanone, 252 Trifoliate orange, 186, 188-189 Trifolium, 216, 309, 310, 316 Triopus, 321 Triticeae, salt tolerance, 30 Triticum aestivum, 13 Triticum monococcum, 13, 16 Triticum turgidum, 6-7, 13, 14, 16 Triticum urartu, 13-14, 19-20 Tropical soils, nitrogen availability in, 355 Tungro disease, 224 UKMO model, 431 Union for the Protection of New Varieties, 222, 223 Uniports, ammonium uptake and, 150 Univoltine herbivores, 242, 244 Urea, 352 Ustilago, 211, 216 Vacuole, nitrate sequestration, 157 Vapor pressure deficit, 57-58 carbon isotope discrimination and, 94, 96, 102, 106-107 in gas-exchange efficiency, 84 transpiration efficiency and, 126-127 water stress and, 128 water-use efficiency and, 87 Varieties diversified, see Crop diversification genetic erosion and, 220 Swiss definition, 220 Vegetable production, crop diversification and, 224 Vegetative propagation, 5-7 Vegetative-reproductive transition, 67-68 water-use efficiency and, 88 Velvetleaf, 309 Vicia, 308 Vigna, 352, 355 Vigor, evapotranspiration and, 125-126 Virus, effects on photosynthesis, 62 Volkamer lemon, 183

Index

Volume, plant, in predicting crop-weed interactions, 300 Water, see also Soil water availability, plant physiology and, 87-91 herbicide contamination, 292 relations in sunflower, 25-27, 131 in wheat, 19, 21 relative plant content, 59 stress dry matter distribution and, 127-130 harvest index and, 130-131 leaf growth and, 26 patterns of, 120 photosynthesis and, 42, 58-59, 79-88 vegetative-reproductive transition and, 67 yield and, 28, 94-111, 127-131 transport, 118; see also Hydraulic conductivity use, optimum biomass allocation and, 131-133 in weed management, 313-314, 318-319 Water-limited environments, see Dryland agricultural systems Water-use efficiency aboveground biomass and, 118 ambient carbon dioxide and, 447-448 canopy, 85-88 carbon isotope discrimination and, 79-80, 92-94, 111 in crop improvement, 79-81 defined, 80, 118 flowering and, 88 leaf, 81-84 in models of global environmental change, 429, 430 nitrogen use and, 59 in photosynthesis, 40, 56, 57-59, 70, 81-84, 85 whole plant, 84-85 yield and, 84 Weather forecasting, 120-122, 137 Weeds, see also Crop-weed interactions; Weed management economic costs, 291 emergence, 298 herbicides and, 291-292 interactions, 328 intercropping with, 270-271 resistance in, 327-328

471

seed predation in, 311-312 spatial distribution, 300-301 traits and characters useful in management, 294-295 Weed management, see also Crop-weed interactions competition and, 325, 328 conventional, 291-292, 329 crop density in, 316, 329 crop rotation in, 307, 327-328, 329 cultivation in, 309, 310-311,328 cumulative actions and, 325-329 fertilizer application and, 314-316, 319 flame weeding in, 311 future directions, 329-330 goals, 293-294, 296 herbicides in, 295, 296, 328, 329 hygiene in, 312 information base of, 294 intercropping in, 317-318 irrigation and, 313-314, 319 in monocultures, 327-328 pathogens and predators used in, 311-312, 320-321 propagule dispersal and, 301,312 rationales for, 292-293 residues in, 307-309, 321-324 shading in, 319-320 soil moisture and, 318-319 soil nitrogen levels and, 316-317 soil solarization and, 312 soil temperatures and, 318 tillage in, 309, 311 weed density in, 298 weed emergence in, 298 weed interactions in, 328 weed resistance and, 327-328 weed suppressive cultivars and, 324-325 weed tolerant cultivars and, 324-325 West Africa, annual burning in, 358 Wheat axial conductance in, 187 biomass, 18 breeding, 98-103 canopy, 16, 18 carbohydrate storage, 66 carbon flow in, 396-397 carbon isotope discrimination and, 95, 97, 98-103 domestication, 6-7 in dryland agricultural systems, 132, 134-137

472

Index

evapotranspiration and, 124, 125-126 fertilizer banding in, 316-317 flag leaf, 15 grain filling, 98 grain size, 19-20 harvest index, 19 intercropping in, 216, 225 leaf rust, 208 model of crop rotation, 136 natural habitats, 13-14 physiology and allocation, 14-21 ploidy levels, 13 preanthesis assimilation, 130 Rht dwarfing genes, 18 stem rust, 207, 212, 225 stripe rust, 205, 225 water stress and, 131 weed suppression by, 324 yield, 11, 16-18, 98-103, 122, 134-137 White clover, in wheat intercropping, 216 Whitefly, 249 Wild plants compared with crops, 12-27 as crop progenitors, 3-5, 48-49 germplasm, 27-31 herbivores and, 242, 243 Willow, photoinhibition in, 56 Wind dispersion, of phytophagous arthropods, 242 Wind speed, photosynthetic rate and, 43, 45 "Woody agriculture," 217

Xanthium, 300 Xanthomonas, 205 Xylem, 161,187-188 Yellow Eye bean, 325 Yield breeding and, 9-12 carbon isotope discrimination and, 94-107, 110-111 components, 131 correlation with southern oscillation index, 122 in dryland agricultural systems, 127-128, 131,131-133, 134-137 dwarfing and, 39 effects of flowering on, 97-98, 110 forecasts, 430, 431-432, 445 gas-exchange efficiency and, 101-102 harvest index and, 131 leaf erectness and, 39 loss, 240, 291,297-299, 319-321 in microorganisms, 371-372 nitrogen and, 23, 348, 353 nitrogen loss in, 351 physiological traits and, 16-17, 28, 89 resource availability and, 8 selection strategies and, 9-12 water-use efficiency and, 84, 98-109 Yield coefficient, 371-372 in soil carbon management, 401 Zaire, partial seed replacement in, 220 Zea, 217, 297 Zingiberene, 252

Physiological Ecology A Series of Monographs, Texts, and Treatises Series Editor Harold A. Mooney

Stanford University,Stanford, California Fakhri A. Bazzaz Robert W. Pearcy

Editorial Board F. Stuart Chapin Martyn M. Caldwell

James R. Ehleringer E.-D. Schulze

T. T. KOZLOWSKI. Growth and Development of Trees, Volumes I and II, 1971 D. HILLEL. Soil and Water: Physical Principles and Processes, 1971 V. B. YOUNGER and C. M. McKELL (Eds.). The Biology and Utilization of Grasses, 1972 J. B. MUDD and T. T. KOZLOWSKI (Eds.). Responses of Plants to Air Pollution, 1975 R. DAUBENMIRE. Plant Geography, 1978 J. LEVITT. Responses of Plants to Environmental Stresses, Second Edition Volume I: Chilling, Freezing, and High Temperature Stresses, 1980 Volume II: Water, Radiation, Salt, and Other Stresses, 1980 A. I_ARSEN (Ed.). The Boreal Ecosystem, 1980 S. A. GAUTHREAUX, JR. (Ed.). Animal Migration, Orientation, and Navigation, 1981 F. J. VERNBERG and W. B. VERNBERG (Eds.). Functional Adaptations of Marine Organisms, 1981 R. D. DURBIN (Ed.). Toxins in Plant Disease, 1981 C. P. LYMAN, J. S. WILLIS, A. MAI_AN, and L. C. H. WANG. Hibernation and Torpor in Mammals and Birds, 1982 T. T. KOZLOWSKI (Ed.). Flooding and Plant Growth, 1984 E. L. RICE. Allelopathy, Second Edition, 1984 ~

474

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M. L. CODY (Ed.). Habitat Selection in Birds, 1985 R.J. HAYNES, K. C. C&MERON, K. M. GOH, and R. R. SHERLOCK (Eds.). Mineral Nitrogen in the Plant-Soil System, 1986 T. T. KOZLOWSKI, P.J. KRAMER, and S. G. PALLARDY. The Physiological Ecology of Woody Plants, 1991 H. A. MOONEY, W. E. WINNER, and E.J. PELL (Eds.). Response of Plants to Multiple Stresses, 1991 F. S. CHAPIN III, R. L. JEFFERIES, J. F. REYNOLDS, G. R. SHAVER, and J. SVOBODA (Eds.). Arctic Ecosystems in a Changing Climate: An Ecophysiological Perspective, 1991 T. D. SHARKEY, E. A. HOLIJkND, and H. A. MOONEY (Eds.). Trace Gas Emissions by Plants, 1991 U. SEELIGER (Ed.). Coastal Plant Communities of Latin America, 1992 JAMES R. EHLERINGER and CHRISTOPHER B. FIELD (Eds.). Scaling Physiological Processes: Leaf to Globe, 1993 JAMES R. EHLERINGER, ANTHONY E. HALL, and GRAHAM D. FARQUHAR (Eds.). Stable Isotopes and Plant Carbon-Water Relations, 1993 E.-D. SCHULZE (Ed.). Flux Control in Biological Systems, 1993 MARTYN M. CALDWELL and ROBERT W. PEARCY (Eds.). Exploitation of Environmental Heterogeneity by Plants: Ecophysiological Processes Above- and Belowground, 1994 WILLIAM K. SMITH and THOMAS M. HINCKLEY (Eds.). Resource Physiology of Conifers: Acquisition, Allocation, and Utilization, 1995 WILLIAM K. SMITH and THOMAS M. HINCKLEY (Eds.). Ecophysiology of Coniferous Forests, 1995 MARGARET D. LOWMAN and NALINI M. NADKARNI (Eds.). Forest Canopies, 1995 BARBARA L. GARTNER (Ed.). Plant Stems: Physiology and Functional Morphology, 1995 GEORGE W. KOCH and HAROLD A. MOONEY (Eds.). Carbon Dioxide and Terrestrial Ecosystems, 1996 CHRISTIAN KORNER and FAKHRI A. BAZZAZ (Eds.). Carbon Dioxide, Populations, and Communities, 1996 THEODORE T. KOZLOWSKI and STEPHEN G. PALLARDY. Growth Control in Woody Plants, 1997 J.J. LANDSBERG and S. T. GOWER. Applications of Physiological Ecology to Forest Management, 1997 FAKHRI A. BAZZAZ and JOHN GRACE (Eds.). Plant Resource Allocation, 1997 LOUISE E. JACKSON (Ed.). Ecology in Agriculture, 1997